Triple
T37515075
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Templar |
E932613
|
entity |
| Predicate | hasPrimaryAttributes |
P205947
|
FINISHED |
| Object | Strength and Intelligence |
—
|
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: Strength and Intelligence | Statement: [Templar, hasPrimaryAttributes, Strength and Intelligence]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPrimaryAttributes Context triple: [Templar, hasPrimaryAttributes, Strength and Intelligence]
-
A.
hasPrimary
Indicates that one entity is designated as the main or most important instance (the primary) in relation to another entity.
-
B.
hasPrimaryAssociation
Indicates that one entity is chiefly or most directly connected, linked, or related to another among possible associations.
-
C.
hasPrimaryCode
Indicates that an entity is associated with its main or most important identifying code among potentially multiple codes.
-
D.
hasPrimaryKey
Indicates that an entity is designated as the main unique identifier (primary key) for another entity in a data or database structure.
-
E.
hasPrimaryFeature
Indicates that an entity possesses a main or most characteristic feature that defines or distinguishes it.
- 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_69f76ec730988190b5aa4f9cb9afd518 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a037cad051c8190b28b354b89208574 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a037a1553e08190bb7424c448cb1f33 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c842b2c819082f1d2db995ac2eb |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:17 p.m.