Triple
T17351511
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aunt May |
E421823
|
entity |
| Predicate | oftenUnawareOf |
P22661
|
FINISHED |
| Object | Peter Parker’s secret identity as Spider-Man |
—
|
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: Peter Parker’s secret identity as Spider-Man | Statement: [Aunt May, oftenUnawareOf, Peter Parker’s secret identity as Spider-Man]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: oftenUnawareOf Context triple: [Aunt May, oftenUnawareOf, Peter Parker’s secret identity as Spider-Man]
-
A.
ignorantOf
chosen
Indicates that one entity lacks knowledge or awareness of another entity or of some specific fact, topic, or situation.
-
B.
oftenUnnamedIn
Indicates that an entity frequently appears in a given context, work, or setting without being explicitly named.
-
C.
notTypically
Indicates that the referenced situation, behavior, or relationship does not usually or normally occur under standard or expected conditions.
-
D.
typicallyLack
Indicates that one entity is characteristically or usually without, or does not possess, another entity or attribute.
-
E.
awareness
Indicates that an entity has conscious knowledge, perception, or understanding of another entity, situation, or fact.
- 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_69d889d520008190a26917a95bf1c2ea |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e43a2ca0708190aae8306ec3a6f2a7 |
completed | April 19, 2026, 2:13 a.m. |
| PD | Predicate disambiguation | batch_69e3b02662d08190a07d0fb5c04b6f33 |
completed | April 18, 2026, 4:24 p.m. |
Created at: April 10, 2026, 5:44 a.m.