Triple
T1016305
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Verna Fields |
E21937
|
entity |
| Predicate | workedOn |
P3
|
FINISHED |
| Object | Targets |
E121554
|
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: Targets | Statement: [Verna Fields, workedOn, Targets]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Targets Context triple: [Verna Fields, workedOn, Targets]
-
A.
Targets
chosen
Targets is a 1968 American thriller film, often praised as an early landmark in New Hollywood cinema, that interweaves the story of an aging horror star with a modern-day sniper rampage.
-
B.
Carrier
Carrier is a leading global brand specializing in heating, ventilation, air conditioning (HVAC), and refrigeration solutions.
-
C.
TNT
TNT is an American cable television network known for airing sports, movies, and original drama programming.
-
D.
The Limited
The Limited is an American retail clothing brand and former mall-based specialty store chain known for its women’s apparel and its role in building the retail empire of the Wexner family.
-
E.
Wild Target
Wild Target is a 2010 British black comedy film about an aging hitman whose life is upended when he protects a quirky young woman, featuring Emily Blunt in a leading role.
- 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_69a493c68e24819080ed0ee8bcfd5ce0 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b7c1e9d08190baf7e81f3777168d |
completed | March 1, 2026, 10:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac4292482c81909bf39cd0bb288599 |
completed | March 7, 2026, 3:21 p.m. |
Created at: March 1, 2026, 7:41 p.m.