Triple
T9089536
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jolon, California |
E217844
|
entity |
| Predicate | missionNearbyInstanceOf |
P26261
|
FINISHED |
| Object | Spanish mission in California |
—
|
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: Spanish mission in California | Statement: [Jolon, California, missionNearbyInstanceOf, Spanish mission in California]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: missionNearbyInstanceOf Context triple: [Jolon, California, missionNearbyInstanceOf, Spanish mission in California]
-
A.
nearbyTo
Indicates that one entity is located close in distance or position to another entity.
-
B.
nearbyFrontier
Indicates that one entity is located close to a boundary or frontier region associated with another entity.
-
C.
missionTo
Indicates that one entity is assigned, directed, or sent to carry out a specific mission involving another entity or location.
-
D.
possiblePlaceOfMission
chosen
Indicates that a location is a plausible or candidate site where a mission may have taken place or could take place.
-
E.
nearbyUse
Indicates that one entity uses or operates another entity that is located nearby or in close physical proximity.
- 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_69ca83d8ab5881909d8fddae363b32b1 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cc965971f88190acffbf204c11832b |
completed | April 1, 2026, 3:51 a.m. |
| PD | Predicate disambiguation | batch_69cc65fc7f408190a5846e29ab3b97e5 |
completed | April 1, 2026, 12:25 a.m. |
Created at: March 30, 2026, 7:14 p.m.