Triple
T26688545
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Islamist uprising in Syria |
E672813
|
entity |
| Predicate | notableMassKilling |
P42677
|
FINISHED |
| Object | large-scale civilian deaths in Hama |
—
|
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: large-scale civilian deaths in Hama | Statement: [Islamist uprising in Syria, notableMassKilling, large-scale civilian deaths in Hama]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableMassKilling Context triple: [Islamist uprising in Syria, notableMassKilling, large-scale civilian deaths in Hama]
-
A.
massacreOccurredIn
Indicates that a massacre took place within the specified location or area.
-
B.
notableMassKillingSite
chosen
Indicates that a place is recognized as a significant location where a mass killing or massacre occurred.
-
C.
massacreAlsoKnownAs
Indicates that a particular massacre is known or referred to by an alternative name or names.
-
D.
massacreOccurred
Indicates that a large-scale, deliberate killing of multiple individuals took place in a specific event or context.
-
E.
majorMassacre
Indicates a relationship where an event involves the large-scale, deliberate killing of many individuals, typically characterized by extreme violence and high casualty numbers.
- 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_69eecda2066c8190a344218afa5e89c1 |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69ff0491409c8190be40f633a58da0b1 |
completed | May 9, 2026, 9:55 a.m. |
| PD | Predicate disambiguation | batch_69ff040bb5cc81909534c7eee85d5e90 |
completed | May 9, 2026, 9:53 a.m. |
Created at: April 27, 2026, 3:24 a.m.