Triple
T75891
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | International Holocaust Remembrance Day |
E1515
|
entity |
| Predicate | hasHashtag |
P2920
|
FINISHED |
| Object | #HolocaustRemembranceDay |
—
|
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: #HolocaustRemembranceDay | Statement: [International Holocaust Remembrance Day, hasHashtag, #HolocaustRemembranceDay]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHashtag Context triple: [International Holocaust Remembrance Day, hasHashtag, #HolocaustRemembranceDay]
-
A.
hasTerm
chosen
Indicates that an entity includes, is associated with, or is defined by a specific term or condition.
-
B.
hasMarker
Indicates that one entity possesses, is associated with, or is identified by a specific marker.
-
C.
hasNotableSubject
Indicates that an entity is associated with a subject that is particularly significant, prominent, or noteworthy in relation to it.
-
D.
hasBeard
Indicates that one entity possesses or displays a beard.
-
E.
hasConcept
Indicates that an entity includes, embodies, or is associated with a particular concept.
- 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_69a24c60d19c8190a1b6c105ca59ef5b |
completed | Feb. 28, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69a25314bd6c81908d1cfd4b83f20049 |
completed | Feb. 28, 2026, 2:29 a.m. |
| PD | Predicate disambiguation | batch_69a24eae77ec81909015906f31f2b62e |
completed | Feb. 28, 2026, 2:10 a.m. |
Created at: Feb. 28, 2026, 2:06 a.m.