Triple
T34478000
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Abū al-Ḥasan |
E885098
|
entity |
| Predicate | linkedPersonProfession |
P35550
|
FINISHED |
| Object | Arabic grammarian |
—
|
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: Arabic grammarian | Statement: [Abū al-Ḥasan, linkedPersonProfession, Arabic grammarian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: linkedPersonProfession Context triple: [Abū al-Ḥasan, linkedPersonProfession, Arabic grammarian]
-
A.
memberProfession
chosen
Indicates that a member or individual holds or practices a particular profession or occupation.
-
B.
relatedProfession
Indicates that two entities have professions that are connected or associated in some meaningful way, such as being in the same field, industry, or professional domain.
-
C.
sharesProfessionWith
Indicates that two entities have the same profession or occupational role.
-
D.
isAssociatedWithProfessionOfBearer
Indicates that one entity is connected to, or involved with, the profession or occupational role held by another entity.
-
E.
partnerInProfession
Indicates that two or more entities share a professional partnership or collaborate together within the same occupation or field.
- 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_69f349c880408190ade571c471ab154a |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69fe21b0cba48190b56c39e9f1c0eafa |
completed | May 8, 2026, 5:47 p.m. |
| PD | Predicate disambiguation | batch_69fe204576848190aecf204e2adba5dc |
completed | May 8, 2026, 5:41 p.m. |
Created at: May 1, 2026, 2:01 a.m.