Triple
T4683479
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hillsborough Stadium |
E103859
|
entity |
| Predicate | HillsboroughDisasterCause |
P58997
|
FINISHED |
| Object | crush in overcrowded pens |
—
|
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: crush in overcrowded pens | Statement: [Hillsborough Stadium, HillsboroughDisasterCause, crush in overcrowded pens]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: HillsboroughDisasterCause Context triple: [Hillsborough Stadium, HillsboroughDisasterCause, crush in overcrowded pens]
-
A.
debatedAsCauseOf
Indicates that one entity is discussed or argued over as a possible cause or origin of another entity.
-
B.
hasCauseOfDestruction
Indicates that one entity is the cause or agent responsible for the destruction or damage of another entity.
-
C.
floodCause
Indicates that one entity is the cause or source of a flood affecting another entity or area.
-
D.
worstAccidentInSystem
Indicates that an accident is the most severe or damaging one within a given system or context.
-
E.
ceilingCollapseFatalities
Indicates that a ceiling collapse event resulted in one or more fatalities.
- 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_69bd43debbf08190b4bc372e286ec234 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd67c9c3c08190a6c4944cdd1362a8 |
completed | March 20, 2026, 3:29 p.m. |
| PD | Predicate disambiguation | batch_69bd6217e0088190836570522e324dc6 |
completed | March 20, 2026, 3:04 p.m. |
| PDg | Predicate description generation | batch_69bd67c895dc8190ba648002ff54424b |
completed | March 20, 2026, 3:29 p.m. |
Created at: March 20, 2026, 1:16 p.m.