Triple
T7083239
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Black Hole of Calcutta |
E165007
|
entity |
| Predicate | numberOfVictimsClaimed |
P74879
|
FINISHED |
| Object | 146 |
—
|
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: 146 | Statement: [Black Hole of Calcutta, numberOfVictimsClaimed, 146]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfVictimsClaimed Context triple: [Black Hole of Calcutta, numberOfVictimsClaimed, 146]
-
A.
numberOfVictimsKilled
Indicates the count of victims who were killed as a result of the referenced event or action.
-
B.
numberOfVictimsClaimedInTestimony
Indicates the quantity of victims that a person asserts or reports in their testimony.
-
C.
numberOfSuspectedVictims
Indicates the count of individuals believed or alleged to be victims in a particular incident, case, or context.
-
D.
numberOfVictimsInjured
Indicates the count of victims who sustained injuries as a result of the event or incident.
-
E.
hasVictims
Indicates that an entity has one or more individuals who have been harmed, injured, or adversely affected by it.
- 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_69c6887d98408190912b9580666b0c1d |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e5102be08190bbde790bfa8fe9e2 |
completed | March 27, 2026, 8:14 p.m. |
| PD | Predicate disambiguation | batch_69c6e1bfcb948190a5ada74fb8c054cb |
completed | March 27, 2026, 8 p.m. |
| PDg | Predicate description generation | batch_69c6e4a15b088190bee9a23e94aaac53 |
completed | March 27, 2026, 8:12 p.m. |
Created at: March 27, 2026, 2:40 p.m.