Triple
T12390428
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Regla de Palo |
E295977
|
entity |
| Predicate | hasRitualObjectMaterial |
P104708
|
FINISHED |
| Object | iron cauldrons |
—
|
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: iron cauldrons | Statement: [Regla de Palo, hasRitualObjectMaterial, iron cauldrons]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRitualObjectMaterial Context triple: [Regla de Palo, hasRitualObjectMaterial, iron cauldrons]
-
A.
hasRitualObject
Indicates that an entity possesses, uses, or is associated with an object specifically employed in a ritual or ceremonial context.
-
B.
hasRitualElements
Indicates that one entity incorporates, contains, or is characterized by ritualistic components, practices, or features associated with formalized ceremonies or rites.
-
C.
hasRitual
Indicates that an entity performs, observes, or is associated with a specific ritual or ceremonial practice.
-
D.
hasRituals
Indicates that one entity performs, observes, or is associated with specific rituals in relation to another entity or context.
-
E.
hasRitualType
Indicates that an entity is associated with, or classified by, a particular type or category of ritual.
- 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_69d6ad9e653c8190b1473c860ee53dae |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d93fd0bcc48190bb1a59a3aaa6bfdf |
completed | April 10, 2026, 6:22 p.m. |
| PD | Predicate disambiguation | batch_69d93ed256788190b704cad171a4824e |
completed | April 10, 2026, 6:17 p.m. |
| PDg | Predicate description generation | batch_69d93fa244148190a960be3ff6f1cf45 |
completed | April 10, 2026, 6:21 p.m. |
Created at: April 8, 2026, 9:54 p.m.