Triple
T24337582
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | نهر العاصي |
E613421
|
entity |
| Predicate | سبب_التسمية_المحتمل |
P7885
|
FINISHED |
| Object | جريانه بعكس اتجاه الأنهار الأخرى في المنطقة |
—
|
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: جريانه بعكس اتجاه الأنهار الأخرى في المنطقة | Statement: [نهر العاصي, سبب_التسمية_المحتمل, جريانه بعكس اتجاه الأنهار الأخرى في المنطقة]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: سبب_التسمية_المحتمل Context triple: [نهر العاصي, سبب_التسمية_المحتمل, جريانه بعكس اتجاه الأنهار الأخرى في المنطقة]
-
A.
nameMeaningHypothesis
Indicates a proposed or inferred meaning associated with a given name.
-
B.
possibleNameEtymology
Indicates a hypothesized or suggested origin or derivation of an entity’s name from another term, source, or linguistic root.
-
C.
reasonForName
chosen
Indicates the explanation or cause behind why an entity has a particular name.
-
D.
سبب التسمية
Indicates the reason or cause behind assigning a particular name to something.
-
E.
etymologyPossibleMeaning
Indicates a possible or hypothesized meaning that an etymological analysis suggests for a word or term.
- 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_69e2d7dcc5a08190b53691130d56cbc4 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f293212a0881908da028e81d26247d |
completed | April 29, 2026, 11:24 p.m. |
| PD | Predicate disambiguation | batch_69f287ad30048190b3ad3613486f277f |
completed | April 29, 2026, 10:35 p.m. |
Created at: April 18, 2026, 1:57 a.m.