Triple
T16360067
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Har HaBayit |
E397285
|
entity |
| Predicate | secondTempleRebuiltUnder |
P4005
|
FINISHED |
| Object | Persian rule |
—
|
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: Persian rule | Statement: [Har HaBayit, secondTempleRebuiltUnder, Persian rule]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: secondTempleRebuiltUnder Context triple: [Har HaBayit, secondTempleRebuiltUnder, Persian rule]
-
A.
rebuiltInDynasty
Indicates that something was reconstructed or significantly renovated during a specified dynasty.
-
B.
rebuiltAsPalace
Indicates that a structure or building was reconstructed or transformed into a palace.
-
C.
firstTempleIn
Indicates that an entity is the earliest or original temple located in a specified place or region.
-
D.
secondTempleDestructionDate
Indicates the date on which the Second Temple in Jerusalem was destroyed.
-
E.
rebuiltUnder
chosen
Indicates that an entity was reconstructed or restored while being subject to the authority, control, or governance of another 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_69d87f2778dc8190aa95c7572db127e6 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e2fad241848190a9f32c7b050f20a5 |
completed | April 18, 2026, 3:30 a.m. |
| PD | Predicate disambiguation | batch_69e226f37ecc819082af58b29b4e39d1 |
completed | April 17, 2026, 12:26 p.m. |
Created at: April 10, 2026, 5:07 a.m.