Triple
T34502105
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | San Pedro Amuzgos |
E885784
|
entity |
| Predicate | hasArtisanalSector |
P134371
|
FINISHED |
| Object | women weavers |
—
|
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: women weavers | Statement: [San Pedro Amuzgos, hasArtisanalSector, women weavers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasArtisanalSector Context triple: [San Pedro Amuzgos, hasArtisanalSector, women weavers]
-
A.
hasRuralEconomySector
Indicates that an entity participates in, contains, or is associated with an economic sector based on rural activities or rural development.
-
B.
hasIndustrialSector
Indicates that an entity is associated with, operates in, or belongs to a particular industrial sector or branch of economic activity.
-
C.
hasNotableCraft
chosen
Indicates that an entity is associated with a particularly significant or distinguished craft, skill, or artisanal practice.
-
D.
hasTypeOfFoodProduction
Indicates that an entity is associated with or involved in a specific kind or method of food production.
-
E.
hasSmallTownIndustry
Indicates that a small town possesses or supports a particular type of industry or industrial activity.
- F. None of above.
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_69f349cc0220819081f154c6964f4dc2 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69fddf721c1481909301a0f379368f10 |
completed | May 8, 2026, 1:04 p.m. |
| PD | Predicate disambiguation | batch_69fddda1ae7c8190b5848ff9a9e39826 |
completed | May 8, 2026, 12:57 p.m. |
Created at: May 1, 2026, 2:01 a.m.