Triple
T8388144
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | James Whitmore |
E197871
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Battleground |
E136812
|
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: Battleground | Statement: [James Whitmore, notableWork, Battleground]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Battleground Context triple: [James Whitmore, notableWork, Battleground]
-
A.
Battleground
chosen
"Battleground" is a World War II drama film written by Paul Vogel that follows a besieged American infantry unit during the Battle of the Bulge.
-
B.
Batalha
Batalha is a Portuguese town best known for its UNESCO-listed Batalha Monastery, a masterpiece of Gothic and Manueline architecture.
-
C.
Battles
Battles is an American experimental rock band known for its complex, rhythmically intricate compositions and innovative use of looping and electronics.
-
D.
Battle for Land
Battle for Land was a Fascist Italy agricultural and land reclamation initiative aimed at increasing arable land and showcasing the regime’s economic and ideological strength.
-
E.
Battlefield Earth
Battlefield Earth is a 2000 science fiction film, based on L. Ron Hubbard’s novel, widely known for its critical and commercial failure and frequent citation as one of the worst movies ever made.
- 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_69ca82f749388190bffbea6dfb509016 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb81090f688190a3a8d1680383c361 |
completed | March 31, 2026, 8:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cde83aac448190b74f65507170a8f7 |
completed | April 2, 2026, 3:53 a.m. |
Created at: March 30, 2026, 6:03 p.m.