Triple
T35797504
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Restoration-era Paris |
E1034872
|
entity |
| Predicate | lawEnforcementCharacteristic |
P90046
|
FINISHED |
| Object | political surveillance |
—
|
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: political surveillance | Statement: [Restoration-era Paris, lawEnforcementCharacteristic, political surveillance]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lawEnforcementCharacteristic Context triple: [Restoration-era Paris, lawEnforcementCharacteristic, political surveillance]
-
A.
policeForceCharacteristic
chosen
Indicates that a specified characteristic, quality, or attribute is associated with a particular police force.
-
B.
lawEnforcementLevel
Indicates the degree or intensity of law enforcement presence, activity, or strictness applied in a given context.
-
C.
lawEnforcementLabel
Indicates that an entity has been designated, tagged, or classified by a law enforcement authority for monitoring, identification, or investigative purposes.
-
D.
lawEnforcementFunction
Indicates that an entity performs, is responsible for, or is associated with official law enforcement duties or activities.
-
E.
policeCharacter
Indicates that one entity serves as a police officer or law-enforcement figure in relation to another entity.
- 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_69f76e169bd081909f16cd8c9ee7870c |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7a25600d48190a3b8197343038068 |
completed | May 3, 2026, 7:30 p.m. |
| PD | Predicate disambiguation | batch_69f7a070e23881909a233370acb57384 |
completed | May 3, 2026, 7:22 p.m. |
Created at: May 3, 2026, 4:06 p.m.