Triple
T36388697
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ol’ Higue |
E896267
|
entity |
| Predicate | defenseAgainst |
P35255
|
FINISHED |
| Object | scattering rice or seeds to delay her |
—
|
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: scattering rice or seeds to delay her | Statement: [Ol’ Higue, defenseAgainst, scattering rice or seeds to delay her]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: defenseAgainst Context triple: [Ol’ Higue, defenseAgainst, scattering rice or seeds to delay her]
-
A.
defenseResult
Indicates the outcome or consequence of a defensive action or strategy in response to an attack or threat.
-
B.
defenseFrequency
Indicates how often a defensive action or protective behavior occurs within a given context or time frame.
-
C.
defense
chosen
Indicates an action or relationship in which an entity protects, guards, or resists against a threat, attack, or criticism from another entity.
-
D.
defenseIncludes
Indicates that a defense strategy, plan, or system contains or incorporates a particular component, measure, or element as part of it.
-
E.
defends
Indicates that one entity protects or supports another entity against attack, criticism, or harm.
- 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_69f76e52e3108190becf70b090ae7bd6 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fb563aec448190875410fb1a3ed624 |
completed | May 6, 2026, 2:54 p.m. |
| PD | Predicate disambiguation | batch_69fb35b9ede881908aaae93a215525df |
completed | May 6, 2026, 12:36 p.m. |
Created at: May 3, 2026, 4:10 p.m.