Triple
T26943027
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nicasio, California |
E678567
|
entity |
| Predicate | originalSpanishName |
P61285
|
FINISHED |
| Object | Rancho Nicasio |
—
|
NE NERFINISHED |
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: Rancho Nicasio | Statement: [Nicasio, California, originalSpanishName, Rancho Nicasio]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originalSpanishName Context triple: [Nicasio, California, originalSpanishName, Rancho Nicasio]
-
A.
hasNameInSpanish
Indicates that an entity is associated with a specific name expressed in the Spanish language.
-
B.
officialNameInSpanish
Indicates the officially recognized name of an entity when expressed in the Spanish language.
-
C.
historicalNameInSpanish
chosen
Indicates that an entity is known or referred to by a particular historical name when expressed in the Spanish language.
-
D.
hasLongNameInSpanish
Indicates that an entity is known by a long or extended name when expressed in the Spanish language.
-
E.
hasOfficialShortNameInSpanish
Indicates that an entity possesses an officially recognized short form of its name expressed in the Spanish language.
- 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_69eeeb4d69588190a7c912164a1c37b3 |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69fd5d48855c8190bd93070b6a00d8b5 |
completed | May 8, 2026, 3:49 a.m. |
| PD | Predicate disambiguation | batch_69fd5c9aabb88190912800d90184a89d |
completed | May 8, 2026, 3:46 a.m. |
Created at: April 27, 2026, 6:19 a.m.