Triple
T26138129
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | تماثيل رمسيس الثاني |
E659436
|
entity |
| Predicate | تتميز_بـ |
P662
|
FINISHED |
| Object | ملامح ملكية صارمة |
—
|
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: ملامح ملكية صارمة | Statement: [تماثيل رمسيس الثاني, تتميز_بـ, ملامح ملكية صارمة]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: تتميز_بـ Context triple: [تماثيل رمسيس الثاني, تتميز_بـ, ملامح ملكية صارمة]
-
A.
characterizedBy
chosen
Indicates that one entity possesses a defining quality, feature, or attribute expressed by another entity.
-
B.
يميز
Indicates that one entity distinguishes, differentiates, or sets something apart from something else.
-
C.
distinguishingTrait
Indicates that a particular characteristic or feature uniquely differentiates one entity from another.
-
D.
typicalFeatures
Indicates that the related entities are characteristic or commonly occurring features or attributes of something.
-
E.
specialAppearance
Indicates that an entity makes a notable or exceptional appearance distinct from its usual or regular presence.
- 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_69ee5bc3c20c8190bf2cf272f4170e95 |
completed | April 26, 2026, 6:38 p.m. |
| NER | Named-entity recognition | batch_69f60be1d2408190820365bf7d8436bd |
completed | May 2, 2026, 2:36 p.m. |
| PD | Predicate disambiguation | batch_69f5f7fd90fc81909055b211368f9139 |
completed | May 2, 2026, 1:11 p.m. |
Created at: April 26, 2026, 8:18 p.m.