Triple
T16354129
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | بین الخدماتی مخابرات |
E397128
|
entity |
| Predicate | usesSymbolOf |
P9907
|
FINISHED |
| Object | پاکستانی فوج |
—
|
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: پاکستانی فوج | Statement: [بین الخدماتی مخابرات, usesSymbolOf, پاکستانی فوج]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesSymbolOf Context triple: [بین الخدماتی مخابرات, usesSymbolOf, پاکستانی فوج]
-
A.
symbolicallyUses
chosen
Indicates that one entity employs another as a symbol or representation to convey meaning, ideas, or associations rather than for its literal or practical function.
-
B.
symbolIs
Indicates that one entity serves as the symbolic representation or sign of another entity.
-
C.
symbolizedIn
Indicates that one entity serves as a symbol or representation of another entity.
-
D.
appearsWithSymbol
Indicates that one entity is shown or presented together with a particular symbol in the same visual or contextual setting.
-
E.
hasSymbolicInterpretation
Indicates that one entity is understood or used as a symbolic representation or metaphorical stand-in for another entity or 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_69d87f26864c819088365ca381a003c2 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e2facd80dc8190b08f0eecbf787240 |
completed | April 18, 2026, 3:30 a.m. |
| PD | Predicate disambiguation | batch_69e226f37ecc819082af58b29b4e39d1 |
completed | April 17, 2026, 12:26 p.m. |
Created at: April 10, 2026, 5:07 a.m.