Triple
T7669517
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Estadio Omnilife |
E173711
|
entity |
| Predicate | hasSecuritySystems |
P2368
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Estadio Omnilife, hasSecuritySystems, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSecuritySystems Context triple: [Estadio Omnilife, hasSecuritySystems, yes]
-
A.
hasEmergencySystems
Indicates that the subject is equipped with or includes systems designed to detect, respond to, or manage emergency situations.
-
B.
hasSecurityArchitecture
Indicates that an entity is associated with or defined by a particular security architecture design or framework.
-
C.
doorSafety
Indicates that a door meets specified safety conditions or standards, such as being secure, unobstructed, and compliant with safety regulations.
-
D.
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.
-
E.
hasCCTV
Indicates that one entity is equipped with or monitored by a CCTV (closed-circuit television) system installed or provided by 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_69c699562484819086752091e3164a27 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c7063dab1881909598b04999b8b690 |
completed | March 27, 2026, 10:35 p.m. |
| PD | Predicate disambiguation | batch_69c7015f7430819099d3ea2781b7cee2 |
completed | March 27, 2026, 10:14 p.m. |
Created at: March 27, 2026, 4 p.m.