Triple
T1647790
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CSV |
E35620
|
entity |
| Predicate | alternativeDelimiters |
P30849
|
FINISHED |
| Object | semicolon |
—
|
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: semicolon | Statement: [CSV, alternativeDelimiters, semicolon]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: alternativeDelimiters Context triple: [CSV, alternativeDelimiters, semicolon]
-
A.
alternativeTransliteration
Indicates that one written form represents an alternative way of transliterating the same original text or name into another script or orthography.
-
B.
alternativeForm
Indicates that one entity is an alternative version, variant, or representation of another entity.
-
C.
separatesBy
Indicates that one entity divides, partitions, or creates a boundary between two or more other entities.
-
D.
usesAdditionalLettersFrom
Indicates that one entity forms or derives its representation by incorporating extra letters taken from another entity beyond those originally present.
-
E.
separates
Indicates that one entity divides, parts, or keeps other entities apart from each other.
- F. None of above. chosen
Provenance (4 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_69a8860568888190a32cd9f70acbba42 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aaa0fbe984819084f8daee81ca9b67 |
completed | March 6, 2026, 9:40 a.m. |
| PD | Predicate disambiguation | batch_69a907ce4dd881909168a1e99505d4ec |
completed | March 5, 2026, 4:34 a.m. |
| PDg | Predicate description generation | batch_69a949509d508190a3a35554996823de |
completed | March 5, 2026, 9:13 a.m. |
Created at: March 4, 2026, 7:29 p.m.