Triple
T4423267
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Henry Crabbe |
E95150
|
entity |
| Predicate | stillInvolvedIn |
P55900
|
FINISHED |
| Object | police investigations |
—
|
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: police investigations | Statement: [Henry Crabbe, stillInvolvedIn, police investigations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: stillInvolvedIn Context triple: [Henry Crabbe, stillInvolvedIn, police investigations]
-
A.
oftenInvolvedWith
Indicates that one entity frequently participates in or is commonly associated with activities, events, or situations involving another entity.
-
B.
involves
Indicates that an entity participates in, is a part of, or is implicated within a particular event, process, or relationship.
-
C.
formerlyInvolved
Indicates that an entity previously participated in or was associated with another entity or activity, but is no longer involved.
-
D.
hasPeopleInvolved
Indicates that certain people participate in, are associated with, or are otherwise involved in the referenced entity or event.
-
E.
fortInvolved
Indicates that a fort is involved or participates in a particular event, action, or relationship between entities.
- 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_69b3453a36908190b95a79a297ca083c |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3554b36a48190a475ac5474bed132 |
completed | March 13, 2026, 12:07 a.m. |
| PD | Predicate disambiguation | batch_69b34f5eabe88190a12b244ea71e46d6 |
completed | March 12, 2026, 11:42 p.m. |
| PDg | Predicate description generation | batch_69b3505a87b4819083fbbd58870e520b |
completed | March 12, 2026, 11:46 p.m. |
Created at: March 12, 2026, 11:30 p.m.