Triple
T23173195
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hitchcock catalogue (H numbers) |
E578915
|
entity |
| Predicate | hasAbbreviation |
P43
|
FINISHED |
| Object | H. |
—
|
NE NERFINISHED |
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: H. | Statement: [Hitchcock catalogue (H numbers), hasAbbreviation, H.]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: H. Context triple: [Hitchcock catalogue (H numbers), hasAbbreviation, H.]
-
A.
H.
chosen
H. is an individual whose given name is represented by the initial "H."
-
B.
H
H is the commonly used abbreviation for the Conservative Party of Norway, a major center-right political party in the country.
-
C.
H
H is a light rail service designation used for one of the lines in Denver’s Regional Transportation District (RTD) rail network.
-
D.
Ha
"Ha" is a track by rapper Juvenile, notable for its distinctive second-person narrative style and repetitive use of the word "ha," from his influential 1998 album *400 Degreez*.
-
E.
Ha
Ha is a character from William Golding’s novel "The Inheritors," representing one of the early hominids whose perspective contrasts with the encroaching modern humans.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e245fd2a388190b814c0dfa15f7148 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f18f31f70081909c977d4e43678a9f |
completed | April 29, 2026, 4:55 a.m. |
Created at: April 17, 2026, 4:04 p.m.