Triple
T2288522
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ħal Saflieni Hypogeum |
E51449
|
entity |
| Predicate | depthBelowStreetLevel |
P16570
|
FINISHED |
| Object | about 10 meters |
—
|
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: about 10 meters | Statement: [Ħal Saflieni Hypogeum, depthBelowStreetLevel, about 10 meters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: depthBelowStreetLevel Context triple: [Ħal Saflieni Hypogeum, depthBelowStreetLevel, about 10 meters]
-
A.
numberOfBasementLevels
Indicates the total count of basement levels associated with a given structure or property.
-
B.
clearanceBelow
Indicates that one entity is positioned at a lower vertical clearance level than another, typically with less space between it and an underlying reference surface.
-
C.
hasUndergroundSection
Indicates that an entity includes a portion or segment that is located below ground level.
-
D.
floorCountIncludingBasement
Indicates the total number of floors in a building, counting all above-ground levels plus any basement levels.
-
E.
depthMetresApprox
chosen
Indicates an approximate measurement of how deep something is in metres, rather than an exact value.
- 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_69a88b09c644819090b503456d96bf70 |
completed | March 4, 2026, 7:42 p.m. |
| NER | Named-entity recognition | batch_69abc2497ce881909b05eb9cec67d9e7 |
completed | March 7, 2026, 6:14 a.m. |
| PD | Predicate disambiguation | batch_69abbdbb9e4c819085fc588626ec7c09 |
completed | March 7, 2026, 5:55 a.m. |
Created at: March 4, 2026, 7:48 p.m.