Triple
T25666082
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Igbo traditional religion |
E643519
|
entity |
| Predicate | associatesAlaWith |
P2830
|
FINISHED |
| Object | earth |
—
|
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: earth | Statement: [Igbo traditional religion, associatesAlaWith, earth]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatesAlaWith Context triple: [Igbo traditional religion, associatesAlaWith, earth]
-
A.
isAssociatedWith
chosen
Indicates that there exists a connection, relationship, or involvement between two entities without specifying its exact nature.
-
B.
associatesStructure
Indicates a relationship where one entity is linked or connected to a particular structure, typically to denote that the structure is relevant, attached, or functionally associated with it.
-
C.
antAssociation
Indicates a relationship in which one entity is associated or interacts in a specific, notable way with ants.
-
D.
associatedWithAssociation
Indicates a relationship where an entity is linked or connected to a particular association or organization.
-
E.
associatedWithSee
Indicates a relationship where one entity is contextually or functionally linked to another through the act or concept of seeing or visual observation.
- 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_69e77e7e45648190a068ed3faa8016ea |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69fd67191cf88190b53ecbf5be3564e9 |
completed | May 8, 2026, 4:31 a.m. |
| PD | Predicate disambiguation | batch_69fd654fdaac81908e67e75194710f06 |
completed | May 8, 2026, 4:23 a.m. |
Created at: April 21, 2026, 7:04 p.m.