Triple
T25433562
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kayles |
E637318
|
entity |
| Predicate | hasMoveEffect |
P139133
|
FINISHED |
| Object | removing pins may split the row into two smaller rows |
—
|
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: removing pins may split the row into two smaller rows | Statement: [Kayles, hasMoveEffect, removing pins may split the row into two smaller rows]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMoveEffect Context triple: [Kayles, hasMoveEffect, removing pins may split the row into two smaller rows]
-
A.
hasEffectIn
Indicates that one entity produces, causes, or exerts an effect within a specified context, system, or environment.
-
B.
movementEffect
Indicates how one entity’s movement causes a change or effect in another entity or in the environment.
-
C.
hasAbilityEffect
Indicates that one entity possesses or produces a specific ability-related effect on another entity or context.
-
D.
hasEffectText
chosen
Indicates that a subject is associated with a textual description specifying its effect or impact.
-
E.
hasSecondaryEffect
Indicates that an action, event, or primary effect produces an additional, indirect, or consequential effect beyond its main intended outcome.
- 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_69e75db6c97081908178383fa632b193 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f65aa07c048190a5df30d53d8f0cf5 |
completed | May 2, 2026, 8:12 p.m. |
| PD | Predicate disambiguation | batch_69f659cc571c819097e51e531961d812 |
completed | May 2, 2026, 8:08 p.m. |
Created at: April 21, 2026, 1:59 p.m.