Triple
T34997429
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | JJB Sports |
E1009576
|
entity |
| Predicate | numberOfJobsLostAtCollapse |
P202063
|
FINISHED |
| Object | over 2,000 |
—
|
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: over 2,000 | Statement: [JJB Sports, numberOfJobsLostAtCollapse, over 2,000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfJobsLostAtCollapse Context triple: [JJB Sports, numberOfJobsLostAtCollapse, over 2,000]
-
A.
numberOfBusinessesDestroyed
Indicates the quantity of businesses that have been destroyed in a given event or context.
-
B.
numberOfWorkersFired
chosen
Indicates the quantity of workers who were dismissed or terminated from their jobs.
-
C.
consequenceOfCollapse
Indicates that one event, state, or condition occurs as a direct result of a collapse.
-
D.
lastMajorCollapse
Indicates the most recent significant breakdown or failure event that occurred in relation to the subject.
-
E.
towerCollapsedIn
Indicates that a tower underwent structural failure and collapsed at or within a specified location 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_69f76dca50dc8190b71f39defe186be8 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a037c8c34f88190ace26f555827f23e |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379ff1ba081908eda86acefcf69fb |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:01 p.m.