Triple
T28729167
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | San Juan Bautista Coixtlahuaca |
E730307
|
entity |
| Predicate | hasColonialMonument |
P201275
|
FINISHED |
| Object | former Dominican convent |
—
|
LITERAL 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: former Dominican convent | Statement: [San Juan Bautista Coixtlahuaca, hasColonialMonument, former Dominican convent]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasColonialMonument Context triple: [San Juan Bautista Coixtlahuaca, hasColonialMonument, former Dominican convent]
-
A.
hasColonialTown
Indicates that one entity possesses, contains, or is associated with a town established or characterized as a colonial settlement.
-
B.
hasColonialCapitalNearby
Indicates that an entity is located close to a city that served as a colonial capital.
-
C.
hasColonialCity
Indicates that an entity possesses or includes a city that was established or significantly developed during a period of colonial rule.
-
D.
hasMonumentAt
Indicates that a monument is located at or associated with a specific place or site.
-
E.
hasColonialArchitecture
Indicates that something features or exhibits architectural characteristics associated with colonial-era design or construction.
- F. None of above. chosen
Provenance (4 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_69f043e91fe48190b73bcd8e08d433e0 |
completed | April 28, 2026, 5:21 a.m. |
| NER | Named-entity recognition | batch_69ffe613c03481909f3043ec8bf0bed9 |
completed | May 10, 2026, 1:57 a.m. |
| PD | Predicate disambiguation | batch_69ffe4a73fb4819091600725a443981a |
completed | May 10, 2026, 1:51 a.m. |
| PDg | Predicate description generation | batch_69ffe6130698819099328fce92bb2784 |
completed | May 10, 2026, 1:57 a.m. |
Created at: April 28, 2026, 5:57 a.m.