Triple
T1017136
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cemetery Hill |
E21955
|
entity |
| Predicate | battleOutcomeRole |
P23442
|
FINISHED |
| Object | helped stabilize Union lines after the first day of battle |
—
|
LITERAL 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: helped stabilize Union lines after the first day of battle | Statement: [Cemetery Hill, battleOutcomeRole, helped stabilize Union lines after the first day of battle]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: battleOutcomeRole Context triple: [Cemetery Hill, battleOutcomeRole, helped stabilize Union lines after the first day of battle]
-
A.
resultOfBattle
Indicates that one entity is the outcome or consequence produced by a specific battle or combat event involving another entity.
-
B.
tacticalOutcome
Indicates the specific result or consequence produced by a particular tactic or tactical action in a given situation.
-
C.
roleDuringConquest
Indicates the specific function, position, or capacity an entity held in relation to a particular conquest event.
-
D.
typeOfVictory
Indicates the specific manner or category in which a victory was achieved.
-
E.
gameOutcome
Indicates the result or final status of a game, such as which side won, lost, or if it ended in a draw.
- F. None of above. chosen
Provenance (4 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_69a4b7c4d488819081d8214ba0a22fe5 |
completed | March 1, 2026, 10:03 p.m. |
| PD | Predicate disambiguation | batch_69a4b7238d4c8190b22d6c2ac0ac4911 |
completed | March 1, 2026, 10:01 p.m. |
| PDg | Predicate description generation | batch_69a4b7a0d0308190a00192aa9062bdaa |
completed | March 1, 2026, 10:03 p.m. |
Created at: March 1, 2026, 7:41 p.m.