Triple
T29337282
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PCR (Police Control Room) Unit |
E743943
|
entity |
| Predicate | handlesNumber |
P8195
|
FINISHED |
| Object | 100 |
—
|
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: 100 | Statement: [PCR (Police Control Room) Unit, handlesNumber, 100]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: handlesNumber Context triple: [PCR (Police Control Room) Unit, handlesNumber, 100]
-
A.
hasNumberCategory
Indicates that an entity is associated with a specific numerical classification or type.
-
B.
containsNumber
Indicates that one entity includes or has at least one numeric value or digit within it.
-
C.
openedAsNumber
Indicates that one entity initiated or accessed another entity in a manner represented or tracked by a numeric value (such as a count or identifier).
-
D.
performsNumber
Indicates that an entity carries out or executes a specific numbered item, such as a task, role, or performance identified by that number.
-
E.
number
chosen
Indicates that one entity is associated with a specific numerical value or count in relation to another entity 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_69f09126cfcc8190899b16fbf3c2bf7b |
completed | April 28, 2026, 10:51 a.m. |
| NER | Named-entity recognition | batch_69f697eabb048190bc01a830f14942c6 |
completed | May 3, 2026, 12:33 a.m. |
| PD | Predicate disambiguation | batch_69f69664142c8190bc695501056b0236 |
completed | May 3, 2026, 12:27 a.m. |
Created at: April 28, 2026, 1:31 p.m.