Triple
T24054870
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | My Lai village |
E595769
|
entity |
| Predicate | massacreVictimsApproximateNumber |
P141262
|
FINISHED |
| Object | 500 |
—
|
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: 500 | Statement: [My Lai village, massacreVictimsApproximateNumber, 500]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: massacreVictimsApproximateNumber Context triple: [My Lai village, massacreVictimsApproximateNumber, 500]
-
A.
massacreCasualtiesEstimate
chosen
Indicates an estimated number of people who were killed or injured as a result of a massacre.
-
B.
numberOfVictimsKilled
Indicates the count of victims who were killed as a result of the referenced event or action.
-
C.
massacreDateApprox
Indicates an approximate or uncertain date on which a massacre occurred.
-
D.
estimatedPrisonersKilled
Indicates the estimated number of prisoners who were killed in a given context or event.
-
E.
numberOfVictimsInMassGraves
Indicates the count of individuals who were killed and buried together in mass graves associated with a particular event or context.
- 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_69e288c184b081909f1f1751fb8e299a |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1d9d551288190a2b3b6c8c4f3c1b5 |
completed | April 29, 2026, 10:13 a.m. |
| PD | Predicate disambiguation | batch_69f1764b1d4c8190b12590c6339c31c1 |
completed | April 29, 2026, 3:08 a.m. |
Created at: April 17, 2026, 10:22 p.m.