Triple
T15325488
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Acre Prison break |
E366397
|
entity |
| Predicate | numberOfIrgunFightersInsidePrison |
P118117
|
FINISHED |
| Object | about 10 |
—
|
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 10 | Statement: [Acre Prison break, numberOfIrgunFightersInsidePrison, about 10]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfIrgunFightersInsidePrison Context triple: [Acre Prison break, numberOfIrgunFightersInsidePrison, about 10]
-
A.
numberOfPrisonersDuringWar
Indicates the count of prisoners held during a specified war or wartime period.
-
B.
estimatedPrisoners
Indicates a relationship where a value represents the estimated number of prisoners associated with a particular entity or context.
-
C.
numberOfJewsArrested
Indicates the quantity of Jewish individuals who were apprehended or taken into custody in a given event or context.
-
D.
estimatedPrisonerCount
Indicates the estimated number of prisoners associated with a particular context, such as a location, time period, or event.
-
E.
hasPrisoners
Indicates that an entity holds or contains one or more individuals who are imprisoned or detained.
- 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_69d85a121520819093dcce999fdefe1a |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03dfd8f048190831b463a2728eafe |
completed | April 16, 2026, 1:40 a.m. |
| PD | Predicate disambiguation | batch_69deca9659f48190b8661df223ce5078 |
completed | April 14, 2026, 11:15 p.m. |
| PDg | Predicate description generation | batch_69decf2e413481909d9180a8d78d2c17 |
completed | April 14, 2026, 11:35 p.m. |
Created at: April 10, 2026, 3:16 a.m.