Triple
T15874076
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Million Dollar Theater |
E384901
|
entity |
| Predicate | LAHCMNumber |
P120863
|
FINISHED |
| Object | 6 |
—
|
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: 6 | Statement: [Million Dollar Theater, LAHCMNumber, 6]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: LAHCMNumber Context triple: [Million Dollar Theater, LAHCMNumber, 6]
-
A.
HSMNumber
Indicates that an entity is associated with a specific Hardware Security Module (HSM) identification number.
-
B.
imoNumber
Indicates that an entity is associated with a specific International Maritime Organization (IMO) identification number used to uniquely identify ships and certain maritime structures.
-
C.
ayahNumber
Indicates the specific verse number assigned to an ayah within a surah or text.
-
D.
ISONumber
Indicates that an entity is associated with, identified by, or conforms to a specific ISO (International Organization for Standardization) number or standard.
-
E.
symbolNumber
Indicates a relationship where a specific numerical identifier is assigned to or associated with a particular symbol.
- F. None of above. chosen
Provenance (4 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_69d86da4e86481909f1325fdc971b5ec |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e174de2cd48190ab18e48c9f051a2a |
completed | April 16, 2026, 11:46 p.m. |
| PD | Predicate disambiguation | batch_69e142c3e18c8190bb7b023f4a0eaebb |
completed | April 16, 2026, 8:12 p.m. |
| PDg | Predicate description generation | batch_69e174da2c2c819099ec46616798245a |
completed | April 16, 2026, 11:46 p.m. |
Created at: April 10, 2026, 4:51 a.m.