Triple
T11496666
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | El Segundo High School |
E272551
|
entity |
| Predicate | city |
P40
|
FINISHED |
| Object | El Segundo |
E52470
|
NE 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: El Segundo | Statement: [El Segundo High School, city, El Segundo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: El Segundo Context triple: [El Segundo High School, city, El Segundo]
-
A.
El Segundo, California
chosen
El Segundo, California is a coastal city in Los Angeles County known for its concentration of aerospace, defense, and technology companies.
-
B.
Martinez-Ybor
Martinez-Ybor is the surname of Vicente Martinez-Ybor, a prominent 19th-century Spanish-Cuban cigar manufacturer and founder of the Ybor City neighborhood in Tampa, Florida.
-
C.
Toa Baja
Toa Baja is a coastal municipality in northern Puerto Rico, known for its proximity to San Juan and its mix of urban, industrial, and residential areas.
-
D.
Las Matas
Las Matas is a residential locality in the Community of Madrid, Spain, known as a suburban area closely linked to and bordering the municipality of Las Rozas de Madrid.
-
E.
Lindavista
Lindavista is a metro station in Mexico City serving the Lindavista neighborhood on the city's rapid transit network.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d6aae1b09881909ce2ded3fa0c14fa |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d85de183f08190abfa36eaabc61dc6 |
completed | April 10, 2026, 2:18 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f018963218819097771032a88688af |
completed | April 28, 2026, 2:16 a.m. |
Created at: April 8, 2026, 9:36 p.m.