Triple
T31645239
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arabhi |
E807567
|
entity |
| Predicate | thaatEquivalentInHindustani |
P172050
|
FINISHED |
| Object | Bilawal |
—
|
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: Bilawal | Statement: [Arabhi, thaatEquivalentInHindustani, Bilawal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: thaatEquivalentInHindustani Context triple: [Arabhi, thaatEquivalentInHindustani, Bilawal]
-
A.
equivalentIn
Indicates that two entities are considered logically or functionally the same in meaning, status, or effect within a given context.
-
B.
equivalentInTibet
Indicates that two entities are considered equivalent or correspond to each other within the context of Tibet.
-
C.
languageEquivalent
Indicates that two linguistic expressions convey the same meaning or function across different languages or language varieties.
-
D.
correspondsToInArabic
Indicates that one entity is the equivalent or matching counterpart of another entity specifically in the Arabic language.
-
E.
hasQuranicEquivalent
Indicates that something has a corresponding or analogous concept, term, or passage found in the Quran.
- 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_69f348d9ce58819093ea2da83cbeeec1 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6a956e9b08190bf83547bba8e8147 |
completed | May 3, 2026, 1:48 a.m. |
| PD | Predicate disambiguation | batch_69f6a757c6e081908e37631e5d8d246b |
completed | May 3, 2026, 1:39 a.m. |
| PDg | Predicate description generation | batch_69f6a8036ab481908019f2f071fa406e |
completed | May 3, 2026, 1:42 a.m. |
Created at: April 30, 2026, 10:50 p.m.