Triple
T4815349
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Santa Lucía metro station |
E107173
|
entity |
| Predicate | hasSecurityStaff |
P22957
|
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: [Santa Lucía metro station, hasSecurityStaff, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSecurityStaff Context triple: [Santa Lucía metro station, hasSecurityStaff, yes]
-
A.
hasSecurityTeam
Indicates that an entity is supported or protected by a designated security team responsible for its safety or security operations.
-
B.
isSecureFacility
Indicates that a facility has protections, controls, and safeguards in place to prevent unauthorized access, tampering, or security breaches.
-
C.
hasSecurityPresence
chosen
Indicates that some form of security personnel, system, or measures are present at or associated with an entity or location.
-
D.
hasSafetyRole
Indicates that an entity holds a responsibility or function related to safety within a given context or system.
-
E.
hasSecurityArea
Indicates that an entity is associated with, assigned to, or falls within a defined security-controlled area or zone.
- 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_69bd43f779448190b92885cb70abb6c2 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6ddd17d881909f7731ff2b460e83 |
completed | March 20, 2026, 3:55 p.m. |
| PD | Predicate disambiguation | batch_69bd6c1dfa3481909d240d50ed0ee38c |
completed | March 20, 2026, 3:47 p.m. |
Created at: March 20, 2026, 1:23 p.m.