Triple
T37745261
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cardinal Bishop of Velletri-Segni |
E940827
|
entity |
| Predicate | seeLocatedNear |
P188992
|
FINISHED |
| Object | Rome |
—
|
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: Rome | Statement: [Cardinal Bishop of Velletri-Segni, seeLocatedNear, Rome]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: seeLocatedNear Context triple: [Cardinal Bishop of Velletri-Segni, seeLocatedNear, Rome]
-
A.
oftenLocatedNear
Indicates that one entity is frequently found in close physical proximity to another entity.
-
B.
locatedNearPass
Indicates that one entity is situated close to a mountain pass or similar passageway.
-
C.
meetsNear
Indicates that two entities meet or come together at a location that is in close proximity to a specified reference point or area.
-
D.
locationOfSee
Indicates a relationship where a particular place is the setting or site in which an act of seeing or visual perception occurs.
-
E.
situatedNextTo
Indicates that one entity is located immediately beside another, with no significant separation between them.
- 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_69f76ee0e32c8190b40a3b4cf590337c |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fbaf48ba148190a8bdfd6846ad0540 |
completed | May 6, 2026, 9:14 p.m. |
| PD | Predicate disambiguation | batch_69fbadf632ec8190b14991c971258307 |
completed | May 6, 2026, 9:09 p.m. |
| PDg | Predicate description generation | batch_69fbaeef9c488190babb546b962b4fb6 |
completed | May 6, 2026, 9:13 p.m. |
Created at: May 3, 2026, 4:19 p.m.