Triple
T6790349
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PCL |
E155914
|
entity |
| Predicate | hasTextualVariant |
P59286
|
FINISHED |
| Object | PCL 5 family |
—
|
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: PCL 5 family | Statement: [PCL, hasTextualVariant, PCL 5 family]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTextualVariant Context triple: [PCL, hasTextualVariant, PCL 5 family]
-
A.
hasTextualCharacter
Indicates that something possesses or exhibits the qualities of written or printed text, such as letters, symbols, or characters.
-
B.
hasTextualBase
Indicates that one entity serves as the underlying textual source or foundation upon which another entity is based or derived.
-
C.
hasVariant
Indicates that one entity exists as an alternative form, version, or variation of another entity.
-
D.
hasVariantReadingsWith
chosen
Indicates a relationship where two textual items are linked because they exhibit differing or alternative readings of (typically) the same underlying content.
-
E.
hasLyricalVariant
Indicates that one item has an alternative version that differs in its lyrics while remaining related to the original.
- 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_69c6881770fc8190972b2906390380f5 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d2acbfc0819081f2d6cebfb91765 |
completed | March 27, 2026, 6:55 p.m. |
| PD | Predicate disambiguation | batch_69c6d0979ce0819094678896da4e3169 |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:15 p.m.