Triple
T13930608
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Almost Christmas |
E334978
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object |
Rachel Kylian
Rachel Kylian is an actress known for her role in the holiday comedy film "Almost Christmas."
|
E1069869
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Rachel Kylian | Statement: [Almost Christmas, castMember, Rachel Kylian]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rachel Kylian Context triple: [Almost Christmas, castMember, Rachel Kylian]
-
A.
Jennifer Giroud
Jennifer Giroud is the wife of French professional footballer Olivier Giroud, known for maintaining a relatively private life despite her husband's high-profile career.
-
B.
Wendie Renard
Wendie Renard is a towering French central defender renowned for her leadership, aerial dominance, and long-term success with both Olympique Lyonnais and the France women’s national team.
-
C.
Sophie Meunier
Sophie Meunier is a scholar known for her work on international political economy, particularly French and European Union trade policy and globalization.
-
D.
Kerian Roussel
Kerian Roussel is an individual notable enough to be specifically cited as a bearer of the surname Roussel.
-
E.
Viviane Wembly
Viviane Wembly is a fictional Oxford professor and descendant of Merlin who becomes a key human ally in the film "Transformers: The Last Knight."
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Rachel Kylian Triple: [Almost Christmas, castMember, Rachel Kylian]
Generated description
Rachel Kylian is an actress known for her role in the holiday comedy film "Almost Christmas."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Rachel Kylian Target entity description: Rachel Kylian is an actress known for her role in the holiday comedy film "Almost Christmas."
-
A.
Jennifer Giroud
Jennifer Giroud is the wife of French professional footballer Olivier Giroud, known for maintaining a relatively private life despite her husband's high-profile career.
-
B.
Wendie Renard
Wendie Renard is a towering French central defender renowned for her leadership, aerial dominance, and long-term success with both Olympique Lyonnais and the France women’s national team.
-
C.
Sophie Meunier
Sophie Meunier is a scholar known for her work on international political economy, particularly French and European Union trade policy and globalization.
-
D.
Kerian Roussel
Kerian Roussel is an individual notable enough to be specifically cited as a bearer of the surname Roussel.
-
E.
Viviane Wembly
Viviane Wembly is a fictional Oxford professor and descendant of Merlin who becomes a key human ally in the film "Transformers: The Last Knight."
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d81c5f739081908bc05b2461f54828 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2cf13b2881908a48058a719d3745 |
completed | April 14, 2026, 12:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7ce8262288190a7e6dd647b1917c1 |
completed | May 3, 2026, 10:38 p.m. |
| NEDg | Description generation | batch_69f9fd5b82f48190b0b89ddca25883cc |
completed | May 5, 2026, 2:23 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f9fea0a9dc8190b5b65dfec9626949 |
completed | May 5, 2026, 2:28 p.m. |
Created at: April 9, 2026, 10:16 p.m.