Triple
T24559272
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2004 Tak Bai incident |
E607607
|
entity |
| Predicate | numberOfDeathsAtScene |
P156323
|
FINISHED |
| Object | 7 |
—
|
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: 7 | Statement: [2004 Tak Bai incident, numberOfDeathsAtScene, 7]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfDeathsAtScene Context triple: [2004 Tak Bai incident, numberOfDeathsAtScene, 7]
-
A.
numberOfPeopleLaterDyingOfInjuriesConsidered
Indicates the number of people who subsequently died from injuries that were previously evaluated or taken into account.
-
B.
numberOfFatalAccidents
Indicates the total count of accidents within a given context that resulted in at least one fatality.
-
C.
numberOfFatalitiesInvestigatedAccident
Indicates the count of deaths that were examined as part of the investigation into a specific accident.
-
D.
numberOfVictimsConfirmed
Indicates the confirmed count of victims associated with an event, incident, or situation.
-
E.
numberOfVictimsInSameEvent
Indicates the count of distinct victims involved in the same specific event or incident.
- 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_69e2c4cae1b88190825e88d5ce8aa61e |
completed | April 17, 2026, 11:39 p.m. |
| NER | Named-entity recognition | batch_69f2a8f4af6481908576473adab9f6bf |
completed | April 30, 2026, 12:57 a.m. |
| PD | Predicate disambiguation | batch_69f2a6b99e7c8190ba7e2dc8729a314a |
completed | April 30, 2026, 12:47 a.m. |
| PDg | Predicate description generation | batch_69f2a846c5bc81909ba50cee483bea91 |
completed | April 30, 2026, 12:54 a.m. |
Created at: April 18, 2026, 2:27 a.m.