Triple
T8860653
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rule XVI |
E210878
|
entity |
| Predicate | hasWorkStatus |
P85048
|
FINISHED |
| Object | part of an unfinished work |
—
|
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: part of an unfinished work | Statement: [Rule XVI, hasWorkStatus, part of an unfinished work]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWorkStatus Context triple: [Rule XVI, hasWorkStatus, part of an unfinished work]
-
A.
hasWorkBy
Indicates that one entity (such as a collection, exhibition, or publication) includes or contains creative works produced by another entity (such as an artist, author, or creator).
-
B.
hasWorkOn
Indicates that one entity is associated with, contributes to, or performs work on another entity (such as a project, task, or artifact).
-
C.
hasWorkDetail
Indicates that an entity is associated with specific information or attributes about its work or job-related details.
-
D.
hasWorkAsSetting
Indicates that a particular work (such as a story, film, or artwork) takes place in or uses a specified location, time, or environment as its setting.
-
E.
hasWorkCount
Indicates the number of works (such as items, creations, or outputs) associated with a given entity.
- 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_69ca838bbddc8190ab546d737e5d350f |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc60e712d08190bfb1c4ba3acaea90 |
completed | April 1, 2026, 12:03 a.m. |
| PD | Predicate disambiguation | batch_69cc5c279ea481908c71756f694b66bf |
completed | March 31, 2026, 11:43 p.m. |
| PDg | Predicate description generation | batch_69cc5cffe8ec819084c12770fe0578f2 |
completed | March 31, 2026, 11:47 p.m. |
Created at: March 30, 2026, 6:50 p.m.