Triple
T12921576
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Unidad de Protección Civil de Tláhuac |
E309134
|
entity |
| Predicate | tieneMisión |
P107026
|
FINISHED |
| Object | prevenir emergencias y desastres en Tláhuac |
—
|
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: prevenir emergencias y desastres en Tláhuac | Statement: [Unidad de Protección Civil de Tláhuac, tieneMisión, prevenir emergencias y desastres en Tláhuac]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tieneMisión Context triple: [Unidad de Protección Civil de Tláhuac, tieneMisión, prevenir emergencias y desastres en Tláhuac]
-
A.
isTargetOfMission
Indicates that an entity is the intended objective or focus of a particular mission or operation.
-
B.
hasNamesakeMission
Indicates that one entity has a mission named after it or sharing its name.
-
C.
hasNotableMission
Indicates that an entity is associated with a mission or undertaking that is considered significant or noteworthy.
-
D.
hadMission
Indicates that an entity (such as a person, organization, or vehicle) was assigned or carried out a specific mission or operation.
-
E.
intendedMission
Indicates that one entity is the planned or designated mission, task, or objective associated with another entity.
- F. None of above. chosen
Provenance (4 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_69d7bdf92b588190acdf2a2291ac4590 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d971e7f6e881908c7bb12283898c80 |
completed | April 10, 2026, 9:55 p.m. |
| PD | Predicate disambiguation | batch_69d96fa9b7708190a9e9fa30f59ff580 |
completed | April 10, 2026, 9:46 p.m. |
| PDg | Predicate description generation | batch_69d9708a86bc8190bcdcf97e845bb413 |
completed | April 10, 2026, 9:50 p.m. |
Created at: April 9, 2026, 5:42 p.m.