Triple
T9937586
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gia |
E193995
|
entity |
| Predicate | editor |
P1954
|
FINISHED |
| Object | Eric A. Sears |
E562384
|
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: Eric A. Sears | Statement: [Gia, editor, Eric A. Sears]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Eric A. Sears Context triple: [Gia, editor, Eric A. Sears]
-
A.
Eric A. Sears
chosen
Eric A. Sears is a film editor known for his work on the 2015 horror-comedy movie "Krampus."
-
B.
Michael T. Sauer
Michael T. Sauer was an American judge best known for presiding over high-profile criminal cases in Los Angeles County.
-
C.
Michael J. Weithorn
Michael J. Weithorn is an American television writer and producer best known for creating and working on several sitcoms, including "Ned and Stacey" and "The King of Queens."
-
D.
Bruce H. Mann
Bruce H. Mann is an American legal historian and Harvard Law School professor known for his scholarship on early American legal and economic history and for being married to U.S. Senator Elizabeth Warren.
-
E.
Jonathan I. Coddington
Jonathan I. Coddington is an American arachnologist and biodiversity scientist known for his research on spider systematics and his leadership roles at the Smithsonian Institution’s National Museum of Natural History.
- 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_69ca82e409348190a393777356b80a2a |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb5e4e19881909879b394090d6629 |
completed | April 2, 2026, 12:18 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69de83df5bf881908d775354ace05e66 |
completed | April 14, 2026, 6:13 p.m. |
Created at: March 30, 2026, 8:44 p.m.