Triple
T2405835
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peter Bogdanovich |
E50274
|
entity |
| Predicate | notableWork |
P4
|
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: [Peter Bogdanovich, notableWork, Targets]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Targets Context triple: [Peter Bogdanovich, notableWork, 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.
Target Center
Target Center is a multi-purpose indoor arena in downtown Minneapolis best known as the home venue for Minnesota’s professional basketball teams.
-
C.
Carrier
Carrier is a leading global brand specializing in heating, ventilation, air conditioning (HVAC), and refrigeration solutions.
-
D.
Tats
The Tats are an Iranian-speaking ethnic group of the eastern Caucasus, primarily living in parts of Azerbaijan and southern Dagestan, with a distinct language and cultural traditions.
-
E.
TNT
TNT is an American cable television network known for airing sports, movies, and original drama programming.
- 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_69a88b0339a88190a1207333cd271cc9 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abc8fb78408190b99fa8b4dfaaa75d |
completed | March 7, 2026, 6:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69aeb3e95334819093923b0c36b968f2 |
completed | March 9, 2026, 11:50 a.m. |
Created at: March 4, 2026, 7:58 p.m.