Triple
T2103364
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tenjo |
E37138
|
entity |
| Predicate | borderingMunicipality |
P33892
|
FINISHED |
| Object | Chía |
E31475
|
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: Chía | Statement: [Tenjo, borderingMunicipality, Chía]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chía Context triple: [Tenjo, borderingMunicipality, Chía]
-
A.
Chía
chosen
Chía is a municipality in the department of Cundinamarca, Colombia, known for its rapid urban growth and proximity to the capital city, Bogotá.
-
B.
Hahnenklee
Hahnenklee is a village in the Harz Mountains of Germany, known as a popular tourist resort for hiking, winter sports, and its distinctive stave church.
-
C.
Peruna
Peruna is the live Shetland pony that serves as the official mascot of Southern Methodist University's athletic teams.
-
D.
Vigna
Vigna is a genus of flowering plants in the legume family that includes several important food crops such as cowpeas and mung beans.
-
E.
Fibra Uno
Fibra Uno is a major Mexican real estate investment trust (FIBRA) that owns and operates a large portfolio of commercial properties across Mexico.
- 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_69a8861828948190924aa30c08806b3a |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69abbdc11a048190ba3bbc60f90f34e1 |
completed | March 7, 2026, 5:55 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae3068189c81909cf76fd1fc2a0fe6 |
completed | March 9, 2026, 2:28 a.m. |
Created at: March 4, 2026, 7:43 p.m.