Triple
T30924254
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ha Mim |
E787813
|
entity |
| Predicate | hasFirstLetterName |
P178779
|
FINISHED |
| Object | Ha |
—
|
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: Ha | Statement: [Ha Mim, hasFirstLetterName, Ha]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFirstLetterName Context triple: [Ha Mim, hasFirstLetterName, Ha]
-
A.
hasLetterName
chosen
Indicates that an entity is associated with a specific letter used as its name or designation.
-
B.
hasInitialLetters
Indicates that one entity’s initial letters or acronym are derived from or correspond to the other entity.
-
C.
hasFirstNameFrom
Indicates that an entity’s first name is derived from, based on, or taken from another specified source.
-
D.
hasFamilyNameInitial
Indicates that an entity’s family name begins with a specified initial letter or character.
-
E.
hasFirstNameOnly
Indicates that the entity is identified or recorded using only a first name, without any additional name components such as a middle or last name.
- 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_69f224bfaca88190b9d0dfcc86297fe9 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fe38be079c8190a240191ac0e73e3a |
completed | May 8, 2026, 7:25 p.m. |
| PD | Predicate disambiguation | batch_69fe350344508190930de2218156ca02 |
completed | May 8, 2026, 7:09 p.m. |
Created at: April 29, 2026, 8:51 p.m.