Triple
T6389592
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Natalie Schafer |
E143787
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Natalie
Natalie is a feminine given name of Latin origin, commonly associated with the meaning "birthday of the Lord" or "Christmas Day."
|
E589569
|
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: Natalie | Statement: [Natalie Schafer, givenName, Natalie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Natalie Context triple: [Natalie Schafer, givenName, Natalie]
-
A.
Natalie
Natalie is the given name of Natalie Evans, Baroness Evans of Bowes Park, a British Conservative politician and life peer.
-
B.
Natalie
Natalie is the central protagonist of the science fiction thriller film "The Darkest Hour," around whom the story’s alien-invasion survival plot revolves.
-
C.
Natalie
Natalie is the central protagonist of the British film "Life Is Sweet," around whom the story’s family and everyday struggles revolve.
-
D.
Natalie
Natalie is a fictional character from the romantic comedy universe of "Love Actually," appearing in the charity sequel short film "Red Nose Day Actually."
-
E.
Nicole
Nicole is a feminine given name of Greek origin meaning "victory of the people," commonly used in many English- and French-speaking countries.
- 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: Natalie Triple: [Natalie Schafer, givenName, Natalie]
Generated description
Natalie is a feminine given name of Latin origin, commonly associated with the meaning "birthday of the Lord" or "Christmas Day."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Natalie Target entity description: Natalie is a feminine given name of Latin origin, commonly associated with the meaning "birthday of the Lord" or "Christmas Day."
-
A.
Natalie
Natalie is a fictional character from the romantic comedy universe of "Love Actually," appearing in the charity sequel short film "Red Nose Day Actually."
-
B.
Natalie
Natalie is the given name of Natalie Evans, Baroness Evans of Bowes Park, a British Conservative politician and life peer.
-
C.
Natalie
Natalie is the central protagonist of the science fiction thriller film "The Darkest Hour," around whom the story’s alien-invasion survival plot revolves.
-
D.
Natalie
Natalie is the central protagonist of the British film "Life Is Sweet," around whom the story’s family and everyday struggles revolve.
-
E.
Nicole
Nicole is a feminine given name of Greek origin meaning "victory of the people," commonly used in many English- and French-speaking countries.
- 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_69c008db906c819096f3597d55d95432 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0686cc6d481909c62a29a84a4ce8e |
completed | March 22, 2026, 10:08 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c638868d4481908611530d0bc8e286 |
completed | March 27, 2026, 7:57 a.m. |
| NEDg | Description generation | batch_69c639320a608190bc1123fe00ac1f9a |
completed | March 27, 2026, 8 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c639f9916c8190a1a9f0284198aebd |
completed | March 27, 2026, 8:04 a.m. |
Created at: March 22, 2026, 4:34 p.m.