Triple
T30743286
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Capitana |
E782747
|
entity |
| Predicate | serviceStartApproximate |
P118961
|
FINISHED |
| Object | early 1500s |
—
|
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: early 1500s | Statement: [Capitana, serviceStartApproximate, early 1500s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: serviceStartApproximate Context triple: [Capitana, serviceStartApproximate, early 1500s]
-
A.
productionStartApproximate
Indicates that the start of production for something is known only approximately rather than as an exact date or time.
-
B.
serviceEntryApproximate
chosen
Indicates that the recorded details of a service entry (such as time, duration, or specifics of the service) are estimated rather than exact.
-
C.
serviceStartLocation
Indicates the place where a service or operation is initiated or begins.
-
D.
runsApproximately
Indicates that an entity performs a running action in a manner that is close to, but not exactly matching, a specified time, distance, speed, or other running-related measure.
-
E.
serviceNumberApproximate
Indicates that one entity’s service number is approximately equal to, but not necessarily exactly the same as, another entity’s service number.
- 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_69f224aeb1588190897d395e8ed2acb8 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f79f48acec8190a9d5964581a94f6c |
completed | May 3, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_69f79e4888248190be2f63cdfb5cd7b7 |
completed | May 3, 2026, 7:13 p.m. |
Created at: April 29, 2026, 8:38 p.m.