Triple
T26176616
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Byblos old souk |
E654559
|
entity |
| Predicate | otherLanguageCommonlyUsed |
P12203
|
FINISHED |
| Object | English |
—
|
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: English | Statement: [Byblos old souk, otherLanguageCommonlyUsed, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: otherLanguageCommonlyUsed Context triple: [Byblos old souk, otherLanguageCommonlyUsed, English]
-
A.
otherLanguage
chosen
Indicates that an entity has or uses an additional language distinct from its primary or main language.
-
B.
languageUsedAs
Indicates that one language is employed in a specific role, function, or context relative to another entity or situation.
-
C.
languageOfSurroundingCulture
Indicates that one entity is the language predominantly used or characteristic of the surrounding culture associated with another entity.
-
D.
languagesSpoken
Indicates that an entity is able to communicate using one or more specified languages.
-
E.
isWidelySpokenIn
Indicates that a language is spoken by a large portion of the population across many regions or communities within a specified area.
- 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_69ee5b45873c81909499203612d05d07 |
completed | April 26, 2026, 6:36 p.m. |
| NER | Named-entity recognition | batch_69f638d11c988190af7fd4572b08e038 |
completed | May 2, 2026, 5:48 p.m. |
| PD | Predicate disambiguation | batch_69f63706b6008190993577193c85ff50 |
completed | May 2, 2026, 5:40 p.m. |
Created at: April 26, 2026, 8:38 p.m.