Triple
T30290448
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Private Daniel Jackson |
E770354
|
entity |
| Predicate | battleParticipatedInFictional |
P76408
|
FINISHED |
| Object | Battle for Ramelle bridge |
—
|
NE NERFINISHED |
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: Battle for Ramelle bridge | Statement: [Private Daniel Jackson, battleParticipatedInFictional, Battle for Ramelle bridge]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: battleParticipatedInFictional Context triple: [Private Daniel Jackson, battleParticipatedInFictional, Battle for Ramelle bridge]
-
A.
capturedInFictionalEvent
Indicates that an entity is depicted as being captured during a fictional event or scenario.
-
B.
battleParticipated
chosen
Indicates that an entity took part in a specific battle as a combatant or participant.
-
C.
hasFictionalWar
Indicates that there exists a fictional or imagined war involving the related entities.
-
D.
battlePartOf
Indicates that a specific battle is a component or segment of a larger military campaign, war, or conflict.
-
E.
associatedWithFictionalEvent
Indicates that an entity has a connection or involvement with a fictional event, such as being based on, inspired by, or participating in that imagined occurrence.
- F. None of above.
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_69f224875c288190a9b96b975006ec4a |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f6810beb688190bd9716c9cfe8f00f |
completed | May 2, 2026, 10:56 p.m. |
| PD | Predicate disambiguation | batch_69f6760216108190bbb708d53a6c2c25 |
completed | May 2, 2026, 10:09 p.m. |
Created at: April 29, 2026, 7:47 p.m.