Triple
T11239730
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | David Loughery |
E266038
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Obsessed |
E738879
|
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: Obsessed | Statement: [David Loughery, notableWork, Obsessed]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Obsessed Context triple: [David Loughery, notableWork, Obsessed]
-
A.
Obsessed
Obsessed is a 2009 psychological thriller film starring Idris Elba, Beyoncé, and Ali Larter about a successful executive whose life unravels when a temp employee becomes dangerously fixated on him.
-
B.
Obsessed
"Obsessed" is a 2009 R&B/pop single by Mariah Carey, known for its confrontational lyrics and catchy hook, widely interpreted as a response to rapper Eminem.
-
C.
Obsessed
"Obsessed" is a country-pop studio album by American duo Dan + Shay, featuring romantic, harmony-rich tracks that helped solidify their mainstream success.
-
D.
Obsessed
"Obsessed" is a crime thriller novel in the Michael Bennett series by James Patterson, following the NYPD detective as he tackles a particularly personal and dangerous case.
-
E.
Obsessed
chosen
Obsessed is a work by creator Ken Seng, recognized as one of his notable contributions to his field.
- 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_69d6aac656d48190b275efaa7d6074ee |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e918375081908c2a7ccb50cbf331 |
completed | April 9, 2026, 5:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e4ad6e9390819085d10635cb039f85 |
completed | April 19, 2026, 10:24 a.m. |
Created at: April 8, 2026, 9:30 p.m.