Triple
T26792508
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mark Twain Tonight! (1967 TV special) |
E670553
|
entity |
| Predicate | includesTextFrom |
P150841
|
FINISHED |
| Object | The Adventures of Tom Sawyer |
—
|
NE NERFINISHED |
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: The Adventures of Tom Sawyer | Statement: [Mark Twain Tonight! (1967 TV special), includesTextFrom, The Adventures of Tom Sawyer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includesTextFrom Context triple: [Mark Twain Tonight! (1967 TV special), includesTextFrom, The Adventures of Tom Sawyer]
-
A.
containsText
Indicates that one entity includes the specified text string within its content.
-
B.
containsTextsFor
Indicates that one entity holds or includes text content intended for use by another entity.
-
C.
hasTextFrom
chosen
Indicates that one entity contains, is derived from, or directly uses the textual content originating from another entity.
-
D.
followsInText
Indicates that one textual element appears immediately or subsequently after another within the same text.
-
E.
includesMatchesFrom
Indicates that one entity contains or aggregates matches or matching results that originate from another source or context.
- 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_69eeb31d45f8819089f52ebdbc556218 |
completed | April 27, 2026, 12:51 a.m. |
| NER | Named-entity recognition | batch_69fd68abf52881909c5a390c362b7c59 |
completed | May 8, 2026, 4:38 a.m. |
| PD | Predicate disambiguation | batch_69fd6812d0c88190930d8fa2d4b92490 |
completed | May 8, 2026, 4:35 a.m. |
Created at: April 27, 2026, 4:17 a.m.