Triple
T21786592
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Radimlja necropolis |
E537852
|
entity |
| Predicate | hasNumberOfTombstones |
P51860
|
FINISHED |
| Object | over 130 |
—
|
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: over 130 | Statement: [Radimlja necropolis, hasNumberOfTombstones, over 130]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfTombstones Context triple: [Radimlja necropolis, hasNumberOfTombstones, over 130]
-
A.
hasApproximateNumberOfTombs
chosen
Indicates that an entity is associated with a tomb count that is approximate rather than exact.
-
B.
hasFormulaOnTombstone
Indicates that a tombstone bears a specific written formula or inscription on it.
-
C.
hasCheckpoint
Indicates that an entity includes, contains, or is associated with one or more intermediate control or verification points within its structure, process, or path.
-
D.
hasApproximateBrickCount
Indicates that an entity is associated with an estimated or non-exact number of bricks.
-
E.
hasNumberOfMonoliths
Indicates the specific count of monoliths associated with a given 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_69e0c47198f881908cb0d237266c10e9 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f0621b5d6881908b74bc999c94fa3d |
completed | April 28, 2026, 7:30 a.m. |
| PD | Predicate disambiguation | batch_69e6be6299988190a34c98fa76d94700 |
completed | April 21, 2026, 12:01 a.m. |
Created at: April 16, 2026, 6:52 p.m.