Triple
T18346600
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UdeC |
E439555
|
entity |
| Predicate | hasCampusIn |
P4623
|
FINISHED |
| Object | Los Ángeles |
—
|
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: Los Ángeles | Statement: [UdeC, hasCampusIn, Los Ángeles]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Los Ángeles Context triple: [UdeC, hasCampusIn, Los Ángeles]
-
A.
Los Ángeles
chosen
Los Ángeles is a mid-sized Chilean city known as an important commercial and agricultural center in the south-central part of the country.
-
B.
Los Angeles
Los Angeles is a major U.S. metropolis known for its entertainment industry, cultural diversity, and sprawling urban landscape.
-
C.
San Angeles
San Angeles is a fictional futuristic megacity formed from the merger of Los Angeles and San Diego in the science fiction film "Demolition Man."
-
D.
Angeles
"Angeles" is a track from Enya’s 1991 new-age album *Shepherd Moons*, known for its ethereal vocals and atmospheric, layered production.
-
E.
Angeles
Angeles is a barangay (village-level administrative division) within the municipality of San Antonio in the province of Zambales, Philippines.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b9175fec8190af865699b4e64d8c |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e514f4740c8190b70ba48a4232953e |
completed | April 19, 2026, 5:46 p.m. |
Created at: April 10, 2026, 10:37 a.m.