Triple
T11516016
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Iraqw |
E273031
|
entity |
| Predicate | hasBasicLexiconSource |
P35713
|
FINISHED |
| Object | Afroasiatic roots |
—
|
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: Afroasiatic roots | Statement: [Iraqw, hasBasicLexiconSource, Afroasiatic roots]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBasicLexiconSource Context triple: [Iraqw, hasBasicLexiconSource, Afroasiatic roots]
-
A.
hasLexiconPreservedIn
Indicates that the lexicon of one entity is preserved, recorded, or stored within another entity.
-
B.
hasLinguisticClassificationSource
chosen
Indicates the source or reference from which a linguistic classification has been derived or documented.
-
C.
hasBasicLetters
Indicates that an entity contains or is composed of fundamental alphabetic characters, without additional symbols or diacritics.
-
D.
hasKnownVocabulary
Indicates that an entity possesses a defined, identifiable set of terms or words that it can recognize or use.
-
E.
hasLinguisticElement
Indicates that one entity includes, is associated with, or is characterized by a particular linguistic component such as a word, phrase, symbol, or other language element.
- 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_69d6aae2c3748190bed2ea50dfb160dc |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d87fcc72a48190b81acedfcc8685d3 |
completed | April 10, 2026, 4:42 a.m. |
| PD | Predicate disambiguation | batch_69d80876e5f0819088cff2e72f773cf6 |
completed | April 9, 2026, 8:13 p.m. |
Created at: April 8, 2026, 9:36 p.m.