Triple
T10433228
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tuquʼ |
E245969
|
entity |
| Predicate | hasAlternativeSpelling |
P457
|
FINISHED |
| Object | Tuqu |
E245969
|
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: Tuqu | Statement: [Tuquʼ, hasAlternativeSpelling, Tuqu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tuqu Context triple: [Tuquʼ, hasAlternativeSpelling, Tuqu]
-
A.
Tuquʼ
chosen
Tuquʼ is a Palestinian town located southeast of Bethlehem in the central West Bank.
-
B.
Tuspa
Tuspa is an alternative name for Tushpa, the ancient capital city of the Urartian kingdom located near modern-day Lake Van in eastern Turkey.
-
C.
Tupiza
Tupiza is a small historic town in southern Bolivia known for its dramatic red-rock canyons and as a gateway to Andean landscapes and mining regions.
-
D.
Tianguá
Tianguá is a municipality in northeastern Brazil known for its location in the highlands of the state of Ceará and its role as a regional commercial and agricultural center.
-
E.
El Quisco
El Quisco is a coastal Chilean town and popular beach resort on the Pacific Ocean, known for its tourism and seaside attractions.
- 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_69d381bf3dc08190bf35a2643e4e8f22 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4ea65afe08190b91260c9267a0f14 |
completed | April 7, 2026, 11:28 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d89f98a2a0819093e029d940c59508 |
completed | April 10, 2026, 6:58 a.m. |
Created at: April 6, 2026, 12:13 p.m.