Triple
T37580415
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | murder of John Lennon |
E934940
|
entity |
| Predicate | numberOfHits |
P42152
|
FINISHED |
| Object | 4 |
—
|
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: 4 | Statement: [murder of John Lennon, numberOfHits, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfHits Context triple: [murder of John Lennon, numberOfHits, 4]
-
A.
approximateNumberOfHits
Indicates that the associated value represents an estimated count of how many times something has been accessed, used, or requested.
-
B.
ALHits
Indicates that a baseball player achieved a hit while playing in an American League (AL) game.
-
C.
includesHits
Indicates that one entity contains or encompasses one or more hits, results, or matching items associated with another entity.
-
D.
numberOfCounts
chosen
Indicates the total quantity or tally of discrete occurrences, items, or instances associated with an entity or event.
-
E.
numberOfTargets
Indicates the quantity of target entities associated with or affected by a given subject or event.
- 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_69f76ece61dc8190a0ab33f8d87d0a7e |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a037c8efcd4819088c2aeead65d93df |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a1553e08190bb7424c448cb1f33 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:17 p.m.