Triple
T13850872
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saint Isabel of Portugal |
E332936
|
entity |
| Predicate | birthPlace |
P1
|
FINISHED |
| Object | Zaragoza |
E55920
|
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: Zaragoza | Statement: [Saint Isabel of Portugal, birthPlace, Zaragoza]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zaragoza Context triple: [Saint Isabel of Portugal, birthPlace, Zaragoza]
-
A.
Zaragoza
Zaragoza is a metro station on Mexico City’s Line 1 that serves as a key eastern access point to the city’s rapid transit network.
-
B.
Zaragoza
chosen
Zaragoza is a historic city in northeastern Spain, known for landmarks like the Basilica del Pilar and its role as a major cultural and economic center in the Aragon region.
-
C.
Zaragoza
Zaragoza is a small municipality and town in the northern Mexican state of Coahuila, known for its rural character and proximity to the U.S. border.
-
D.
Zaragoza
Zaragoza is a barangay (village-level administrative division) within the municipality of Oton in the province of Iloilo, Philippines.
-
E.
Zaragosa
Zaragosa is a barangay (village-level administrative division) within the municipality of Badian in the province of Cebu, Philippines.
- 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_69d81c5ba13c8190839315f54768acfd |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de02d8fb788190baef7537be2baecb |
completed | April 14, 2026, 9:03 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fbac802b7081909b36eebe85374594 |
completed | May 6, 2026, 9:02 p.m. |
Created at: April 9, 2026, 10:14 p.m.