Triple
T327249
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yasser Arafat |
E6545
|
entity |
| Predicate | hasParticularSign |
P9766
|
FINISHED |
| Object | distinctive black-and-white keffiyeh |
—
|
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: distinctive black-and-white keffiyeh | Statement: [Yasser Arafat, hasParticularSign, distinctive black-and-white keffiyeh]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasParticularSign Context triple: [Yasser Arafat, hasParticularSign, distinctive black-and-white keffiyeh]
-
A.
hasSign
chosen
Indicates that an entity possesses, displays, or is associated with a particular sign or symbol.
-
B.
starSign
Indicates the astrological zodiac sign associated with a person or entity based on their birth date.
-
C.
hasPar
Indicates a relationship where one entity has another entity as its parent.
-
D.
hasTypeOfInsignia
Indicates that an entity bears or is associated with a specific kind or category of insignia.
-
E.
hasInsigniaWornBy
Indicates that a particular insignia is worn by a specified entity (such as a person, group, or organization).
- 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_69a2e7933d6c8190bb2592ad13286ef2 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2ea98fa2c8190a5b44f4a26543a17 |
completed | Feb. 28, 2026, 1:16 p.m. |
| PD | Predicate disambiguation | batch_69a2e94aab1c8190b8654708c87eeb91 |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.