Triple
T3344997
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dallas Fire-Rescue Department |
E70351
|
entity |
| Predicate | hasOperationalRole |
P11687
|
FINISHED |
| Object | first responder |
—
|
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: first responder | Statement: [Dallas Fire-Rescue Department, hasOperationalRole, first responder]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOperationalRole Context triple: [Dallas Fire-Rescue Department, hasOperationalRole, first responder]
-
A.
hasOrganizationalRole
Indicates that an entity holds a specific role, position, or function within an organization.
-
B.
hasNotableRoleIn
Indicates that an entity holds a significant or noteworthy role or function within another entity, event, work, or context.
-
C.
hasProductionRole
Indicates that an entity holds a specific role or function in the production or creation process of another entity.
-
D.
hasLegalRole
Indicates that an entity holds a specific legal capacity, status, or function in relation to another entity or context.
-
E.
servesRole
chosen
Indicates that one entity performs, fulfills, or occupies a particular function, position, or responsibility 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_69ad85a405e48190b6e68de7cf9f319e |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb1f36c74819093ef2c74a46c2351 |
completed | March 8, 2026, 5:29 p.m. |
| PD | Predicate disambiguation | batch_69ada42df1d48190874bb05f95deefde |
completed | March 8, 2026, 4:30 p.m. |
Created at: March 8, 2026, 3:12 p.m.