Triple
T613148
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frances |
E12143
|
entity |
| Predicate | hasShortForm |
P43
|
FINISHED |
| Object |
Fran
Fran is a common shortened given name, typically used as a diminutive of Frances or Francis.
|
E77813
|
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: Fran | Statement: [Frances, hasShortForm, Fran]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fran Context triple: [Frances, hasShortForm, Fran]
-
A.
The French
The French is a renowned fine-dining restaurant in Manchester’s Midland Hotel, known for its modern British cuisine and historic, elegant setting.
-
B.
France
France is a major Western European nation known for its influential history, culture, and economy, and as a founding member of the European Union and the United Nations.
-
C.
Jean
Jean is the given first name of Henry Dunant, the Swiss humanitarian who founded the Red Cross and received the first Nobel Peace Prize.
-
D.
France Ô
France Ô was a French public television channel dedicated to programming from France’s overseas departments and territories, operated by the France Télévisions group.
-
E.
France 4
France 4 is a French public television channel, part of the France Télévisions group, known for broadcasting youth-oriented and family entertainment programming.
- 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: Fran Triple: [Frances, hasShortForm, Fran]
Generated description
Fran is a common shortened given name, typically used as a diminutive of Frances or Francis.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Fran Target entity description: Fran is a common shortened given name, typically used as a diminutive of Frances or Francis.
-
A.
The French
The French is a renowned fine-dining restaurant in Manchester’s Midland Hotel, known for its modern British cuisine and historic, elegant setting.
-
B.
France
France is a major Western European nation known for its influential history, culture, and economy, and as a founding member of the European Union and the United Nations.
-
C.
Jean
Jean is the given first name of Henry Dunant, the Swiss humanitarian who founded the Red Cross and received the first Nobel Peace Prize.
-
D.
France Ô
France Ô was a French public television channel dedicated to programming from France’s overseas departments and territories, operated by the France Télévisions group.
-
E.
France 4
France 4 is a French public television channel, part of the France Télévisions group, known for broadcasting youth-oriented and family entertainment programming.
- 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_69a493309df48190a327f748e88049a6 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49e08dbf88190ab050078a63e266b |
completed | March 1, 2026, 8:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a563c40fbc81908b117bc6139507d2 |
completed | March 2, 2026, 10:17 a.m. |
| NEDg | Description generation | batch_69a5644ac23c8190b4df2a9f96385fe0 |
completed | March 2, 2026, 10:19 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a564c7011c81908560b563a4cad560 |
completed | March 2, 2026, 10:21 a.m. |
Created at: March 1, 2026, 7:35 p.m.