Triple
T26041075
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paris |
E647691
|
entity |
| Predicate | relatedCore |
P37
|
FINISHED |
| Object | Newcastle |
—
|
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: Newcastle | Statement: [Paris, relatedCore, Newcastle]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relatedCore Context triple: [Paris, relatedCore, Newcastle]
-
A.
relatedPass
Indicates that one pass is associated with or connected to another pass in some relevant way.
-
B.
relatedIntermediate
Indicates an indirect or intermediate relationship between two entities, typically via one or more other entities or steps rather than a direct connection.
-
C.
relatedTo
chosen
Indicates a general, non-specific relationship or association exists between two entities.
-
D.
relatedRoot
Indicates that one entity is connected to another through a shared or common root, origin, or foundational source.
-
E.
relatedCorrespondence
Indicates that there exists a piece of correspondence (such as a letter, email, or message) that is associated with or pertains to the related entity.
- 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_69e77e8c88f08190858c4c81bd2e1b9a |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69fdb04ed81c8190b8feea90c1c785a6 |
completed | May 8, 2026, 9:43 a.m. |
| PD | Predicate disambiguation | batch_69fda9d6c5148190a63205b6d9b0a1b4 |
completed | May 8, 2026, 9:16 a.m. |
Created at: April 22, 2026, 9:08 a.m.