Triple
T14329353
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Another Me |
E355300
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object | Fay |
E965082
|
NE FINISHED |
How this triple was built (2 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: Fay | Statement: [Another Me, mainCharacter, Fay]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fay Context triple: [Another Me, mainCharacter, Fay]
-
A.
Fay
Fay is a given name most famously associated with Canadian-American actress Fay Wray, the iconic star of the 1933 film "King Kong."
-
B.
Fay
chosen
Fay is an American television sitcom created by Susan Harris that aired briefly in the 1970s and centered on the life of a recently divorced woman starting over.
-
C.
Fay
Fay is a common informal nickname for the city of Fayetteville, Arkansas.
-
D.
Faydi
Faydi is a village located within the Shekhan District in the Kurdistan Region of northern Iraq.
-
E.
Faye Greener
Faye Greener is a vain, ambitious aspiring actress in Hollywood and a central figure whose illusions and manipulations drive much of the drama in "The Day of the Locust."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d8278fa2108190bc0d0e7939c1eb03 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de8c1def0081908f03cda8e84d20c0 |
completed | April 14, 2026, 6:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd46927af48190b91095d852fcacbe |
completed | May 8, 2026, 2:12 a.m. |
Created at: April 10, 2026, 1:13 a.m.