Triple
T5260606
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of Ai |
E118812
|
entity |
| Predicate | numberOfAmbushers |
P5177
|
FINISHED |
| Object | about 30,000 men (biblical account) |
—
|
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: about 30,000 men (biblical account) | Statement: [Battle of Ai, numberOfAmbushers, about 30,000 men (biblical account)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfAmbushers Context triple: [Battle of Ai, numberOfAmbushers, about 30,000 men (biblical account)]
-
A.
numberOfAttacks
Indicates the count of distinct attack events associated with a given entity or interaction.
-
B.
numberOfInvaders
chosen
Indicates the quantity of entities classified as invaders associated with a given subject or context.
-
C.
numberOfHostages
Indicates the quantity of hostages involved in a particular situation, event, or context.
-
D.
numberOfTroopsInvolved
Indicates the quantity of military personnel participating in or assigned to a specific operation, event, or engagement.
-
E.
numberOfBombs
Indicates the quantity of bombs associated with a given entity or situation.
- 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_69bd446a42c88190b7ecbef006561d55 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7bcf026c8190881b6e14b962a3c9 |
completed | March 20, 2026, 4:54 p.m. |
| PD | Predicate disambiguation | batch_69bd77c55224819096c0bcfcfae79bd3 |
completed | March 20, 2026, 4:37 p.m. |
Created at: March 20, 2026, 1:50 p.m.