Triple
T276475
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fields Corner |
E5259
|
entity |
| Predicate | hasSafetyFeatures |
P2368
|
FINISHED |
| Object | CCTV 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: CCTV surveillance | Statement: [Fields Corner, hasSafetyFeatures, CCTV surveillance]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSafetyFeatures Context triple: [Fields Corner, hasSafetyFeatures, CCTV surveillance]
-
A.
securityFeature
chosen
Indicates that an entity provides, embodies, or is associated with a mechanism or property intended to enhance safety, protection, or defense against threats or vulnerabilities.
-
B.
hasInteriorFeature
Indicates that an entity contains or includes a specific feature within its interior space.
-
C.
hasNotableFeature
Indicates that an entity possesses a specific characteristic, trait, or attribute that is considered significant or noteworthy.
-
D.
hasFaregates
Indicates that an entity is equipped with or contains faregates used to control or validate access, typically for paid entry.
-
E.
hasCheckAndBalanceWith
Indicates that two entities mutually monitor, limit, or counterbalance each other's powers or actions to prevent dominance or abuse.
- 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_69a257e6c8788190987dfe705ca2912a |
completed | Feb. 28, 2026, 2:50 a.m. |
| NER | Named-entity recognition | batch_69a25dec53ac8190912f3d79576131fa |
completed | Feb. 28, 2026, 3:15 a.m. |
| PD | Predicate disambiguation | batch_69a25b7480e881909399beccfc7ffb81 |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 2:59 a.m.