Triple
T10553307
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Portuguese-Israelite cemetery Beth Haim |
E249008
|
entity |
| Predicate | hasGravestonesFromCentury |
P87860
|
FINISHED |
| Object | 17th century |
—
|
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: 17th century | Statement: [Portuguese-Israelite cemetery Beth Haim, hasGravestonesFromCentury, 17th century]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGravestonesFromCentury Context triple: [Portuguese-Israelite cemetery Beth Haim, hasGravestonesFromCentury, 17th century]
-
A.
hasGraveMarkersFromPeriod
chosen
Indicates that an entity possesses grave markers that date from, or are associated with, a specified historical period.
-
B.
hasGraveOrMemorialOf
Indicates that a location or object serves as the grave or memorial site dedicated to a particular person or entity.
-
C.
hasGravestone
Indicates that one entity possesses, is associated with, or is commemorated by a gravestone.
-
D.
usedAsCemeterySince
Indicates that a place has functioned as a cemetery starting from a specified point in time.
-
E.
numberOfHeadstones
Indicates the total count of headstones associated with a given entity or location.
- 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_69d381c733c08190ab1dd6239f5f34ae |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d52710869c81909b6db1a190825bad |
completed | April 7, 2026, 3:47 p.m. |
| PD | Predicate disambiguation | batch_69d518fa0b4081909bffc936d78bd77b |
completed | April 7, 2026, 2:47 p.m. |
Created at: April 6, 2026, 12:34 p.m.