Triple
T9274148
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lupanar of Pompeii |
E222900
|
entity |
| Predicate | hasGraffitiContent |
P68894
|
FINISHED |
| Object | prices for sexual services |
—
|
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: prices for sexual services | Statement: [Lupanar of Pompeii, hasGraffitiContent, prices for sexual services]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGraffitiContent Context triple: [Lupanar of Pompeii, hasGraffitiContent, prices for sexual services]
-
A.
hasStreetArtStyle
Indicates that something exhibits characteristics or aesthetics associated with a particular style of street art.
-
B.
hasCarvings
Indicates that one entity features or contains carved designs or engravings on its surface, created by another entity or process.
-
C.
hasSpray
Indicates that one entity possesses, contains, or is equipped with a spray or spraying capability in relation to another entity or context.
-
D.
hasArtFeature
chosen
Indicates that an entity possesses or is characterized by a particular artistic attribute, element, or stylistic feature.
-
E.
streetArt
Indicates that an entity creates, displays, or is associated with artistic works placed in public urban spaces, typically on streets or buildings.
- 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_69ca841ffe208190aa7bcffbef2f8379 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd0788e87c81909ccda40d94cc6705 |
completed | April 1, 2026, 11:54 a.m. |
| PD | Predicate disambiguation | batch_69cc7a537bbc8190baee71f556e52a7b |
completed | April 1, 2026, 1:52 a.m. |
Created at: March 30, 2026, 7:33 p.m.