Triple
T5960255
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Obelisk of the Quirinal |
E132616
|
entity |
| Predicate | monumentCategory |
P25584
|
FINISHED |
| Object | ancient monument in Rome |
—
|
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: ancient monument in Rome | Statement: [Obelisk of the Quirinal, monumentCategory, ancient monument in Rome]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: monumentCategory Context triple: [Obelisk of the Quirinal, monumentCategory, ancient monument in Rome]
-
A.
monumentType
chosen
Indicates the specific kind or category of monument that an entity is classified as.
-
B.
monumentGroup
Indicates that one monument belongs to, or is categorized within, a specific group or collection of monuments.
-
C.
monumentSubject
Indicates that the subject serves as the monument or commemorative structure associated with another entity.
-
D.
otherMonuments
Indicates that there exists a relationship between an entity and additional monuments that are associated with or related to it in some relevant way.
-
E.
builtMonument
Indicates that one entity constructed or created a monument in honor of, or related to, another 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_69c0086c2364819091e9fe2f58fa2517 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c03fb7f8a88190a8bd45208bda4a03 |
completed | March 22, 2026, 7:15 p.m. |
| PD | Predicate disambiguation | batch_69c0335a635881909c58c1ef0f97f1e8 |
completed | March 22, 2026, 6:22 p.m. |
Created at: March 22, 2026, 4:02 p.m.