Triple
T23837272
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AMPS firewall paradox |
E590887
|
entity |
| Predicate | influencedWorkOn |
P1994
|
FINISHED |
| Object | ER=EPR conjecture |
—
|
NE NERFINISHED |
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: ER=EPR conjecture | Statement: [AMPS firewall paradox, influencedWorkOn, ER=EPR conjecture]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: influencedWorkOn Context triple: [AMPS firewall paradox, influencedWorkOn, ER=EPR conjecture]
-
A.
influencedWork
chosen
Indicates that one work has had a significant impact on the creation, style, content, or development of another work.
-
B.
wereInfluencedBy
Indicates that one entity’s ideas, actions, or characteristics were shaped or affected by another entity.
-
C.
hadInfluenceOn
Indicates that one entity affected, shaped, or contributed to the development, behavior, or characteristics of another entity.
-
D.
influencedIn
Indicates that one entity had an effect on or shaped another entity within a specific context, domain, or setting.
-
E.
influencedPerson
Indicates that one entity has affected, shaped, or guided the thoughts, behavior, or development of another person.
- 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_69e25d1de32c8190a907afe9c3d6cd6d |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1c883c7108190b3cce6fec0b8609a |
completed | April 29, 2026, 8:59 a.m. |
| PD | Predicate disambiguation | batch_69f156036ad48190bc2ffdaf39218bcb |
completed | April 29, 2026, 12:51 a.m. |
Created at: April 17, 2026, 8:07 p.m.