Triple
T13180113
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2004 DW |
E313699
|
entity |
| Predicate | discoveryDesignation |
P51634
|
FINISHED |
| Object | 2004 DW |
—
|
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: 2004 DW | Statement: [2004 DW, discoveryDesignation, 2004 DW]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: discoveryDesignation Context triple: [2004 DW, discoveryDesignation, 2004 DW]
-
A.
hasDiscoveryDesignation
chosen
Indicates that an entity has been assigned a specific designation or label associated with its discovery.
-
B.
associatedDesignation
Indicates that one entity is linked to or identified by a particular designation, title, or label connected with it.
-
C.
exampleDesignation
Indicates that one entity is identified or labeled as a representative or illustrative instance of another entity.
-
D.
earthDesignation
Indicates that an entity has a specific name or label assigned to it for use in an Earth-based or human-centric context.
-
E.
religiousDesignation
Indicates the specific religious role, status, or affiliation assigned to an 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_69d806ae1e08819090d95bfe1538cc17 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98cf054f88190b05ced98d5a22a62 |
completed | April 10, 2026, 11:51 p.m. |
| PD | Predicate disambiguation | batch_69d98bc2c0c88190be357811aa8e828d |
completed | April 10, 2026, 11:46 p.m. |
Created at: April 9, 2026, 9:14 p.m.