Triple
T2261184
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dyckman Street (A line) |
E50041
|
entity |
| Predicate | hasMosaicNameTablet |
P37521
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Dyckman Street (A line), hasMosaicNameTablet, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMosaicNameTablet Context triple: [Dyckman Street (A line), hasMosaicNameTablet, yes]
-
A.
hasMosaicsBy
Indicates that something contains or features mosaics that were created by a specified agent or creator.
-
B.
hasMuseumName
Indicates that an entity (typically a museum) is associated with a specific name or title.
-
C.
hasCoverName
Indicates that one entity uses or is known by an alternative, often secret or assumed, name in relation to another entity or context.
-
D.
hasChamberName
Indicates that an entity is associated with or identified by a specific chamber name.
-
E.
hasMythicMotif
Indicates that one entity features, embodies, or is associated with a particular mythic motif found in the other 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_69a88b01e0048190ba96431b5f990ba9 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abc2ea65288190bc8644a07a11dfa9 |
completed | March 7, 2026, 6:17 a.m. |
| PD | Predicate disambiguation | batch_69abbdb592588190ac1ef5e8c54575b1 |
completed | March 7, 2026, 5:55 a.m. |
| PDg | Predicate description generation | batch_69abc2e97eb0819084acb26cfa4e3946 |
completed | March 7, 2026, 6:17 a.m. |
Created at: March 4, 2026, 7:48 p.m.