Triple
T28668219
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Abdul Alhazred |
E725637
|
entity |
| Predicate | fictionalBirthCountry |
P49113
|
FINISHED |
| Object | Yemen |
—
|
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: Yemen | Statement: [Abdul Alhazred, fictionalBirthCountry, Yemen]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fictionalBirthCountry Context triple: [Abdul Alhazred, fictionalBirthCountry, Yemen]
-
A.
fictionalBirthPlace
chosen
Indicates the fictional location where a character or entity is described as having been born within a narrative or imagined context.
-
B.
locatedInFictionalCountry
Indicates that an entity exists or is situated within a country that is fictional rather than real.
-
C.
fictionalCountryMentioned
Indicates that a fictional or imaginary country is referenced or discussed in relation to an entity.
-
D.
countryOfOriginFictional
Indicates that a fictional work, character, or element originates from or is associated with a particular country within its narrative or setting.
-
E.
countryOfFictionalContext
Indicates that a work of fiction is primarily set in, or contextually associated with, a particular country.
- 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_69f01d85be388190b669a0e401e2f2c4 |
completed | April 28, 2026, 2:37 a.m. |
| NER | Named-entity recognition | batch_69f7be53890081909b1d93f30a8f31c6 |
completed | May 3, 2026, 9:29 p.m. |
| PD | Predicate disambiguation | batch_69f7bccacbac8190978976324c67db28 |
completed | May 3, 2026, 9:23 p.m. |
Created at: April 28, 2026, 5:02 a.m.