Triple
T19468997
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pallas’ sword-belt |
E487071
|
entity |
| Predicate | recognitionEffectOn |
P136045
|
FINISHED |
| Object | Aeneas’ emotional state |
—
|
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: Aeneas’ emotional state | Statement: [Pallas’ sword-belt, recognitionEffectOn, Aeneas’ emotional state]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: recognitionEffectOn Context triple: [Pallas’ sword-belt, recognitionEffectOn, Aeneas’ emotional state]
-
A.
recognizesImpactOn
Indicates that one entity acknowledges or understands the effect or consequences it has on another entity or situation.
-
B.
encodingImpact
Indicates how one encoding or encoding choice affects, modifies, or constrains another process, representation, or outcome.
-
C.
influencedPerceptionOf
Indicates that one entity has affected, shaped, or altered how another entity is perceived or understood.
-
D.
effectOnUser
Indicates how an action, event, or condition influences or impacts a user.
-
E.
recognizedSee
Indicates that one entity sees another and consciously recognizes or identifies what is being seen.
- 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_69d8e8d86d608190bd199a98d0297f27 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e633e6fd988190b79be580b65746fe |
completed | April 20, 2026, 2:10 p.m. |
| PD | Predicate disambiguation | batch_69e4fd7499a4819082bec0be8afba35c |
completed | April 19, 2026, 4:06 p.m. |
| PDg | Predicate description generation | batch_69e5004d3a708190a1c13c8f644f3926 |
completed | April 19, 2026, 4:18 p.m. |
Created at: April 10, 2026, 1:39 p.m.