Triple
T11843681
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | XSC |
E281717
|
entity |
| Predicate | servesLocalPopulation |
P79065
|
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: [XSC, servesLocalPopulation, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servesLocalPopulation Context triple: [XSC, servesLocalPopulation, yes]
-
A.
servesPopulationCentre
chosen
Indicates that one entity provides services or functions in support of a particular population centre.
-
B.
servesCitizensOf
Indicates that an entity provides services, support, or functions on behalf of the citizens of a specified place or jurisdiction.
-
C.
servesTownship
Indicates that an entity provides official services or administrative functions to a particular township.
-
D.
servesRuralArea
Indicates that an entity provides services or support specifically to people or communities located in rural areas.
-
E.
nearbyCityServed
Indicates that a city is geographically close enough to another city to be considered within its service or support area.
- 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_69d6ab287ba48190a5178779fd19b9b7 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a65a597c8190b09f57463b279afc |
completed | April 10, 2026, 7:27 a.m. |
| PD | Predicate disambiguation | batch_69d8a254a57481908a1e6ad97919c416 |
completed | April 10, 2026, 7:10 a.m. |
Created at: April 8, 2026, 9:43 p.m.