Triple
T7724146
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ma |
E175086
|
entity |
| Predicate | romanizes |
P2508
|
FINISHED |
| Object | 马 |
—
|
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: 马 | Statement: [Ma, romanizes, 马]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: romanizes Context triple: [Ma, romanizes, 马]
-
A.
hasRomanizationOf
chosen
Indicates that one entity is a romanized representation (written in the Latin alphabet) of the other entity’s original script form.
-
B.
romanizationBegan
Indicates that the process of converting text from one writing system into its representation using the Roman (Latin) alphabet was initiated.
-
C.
partlyRomanized
Indicates that an entity has been converted into the Roman (Latin) script only in part, with some portions remaining in another script or unchanged.
-
D.
hasRomanizationStandard
Indicates that an entity’s romanized form follows a specified romanization standard or system.
-
E.
formerTransliteration
Indicates that one transliteration was previously used for an entity but has since been replaced by a different transliteration.
- 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_69c6995d541c81909eaa646b1a8369a9 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c7074eca4c8190bd51fd1b450729e8 |
completed | March 27, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69c7016a6cf88190b53bf4b958f0f302 |
completed | March 27, 2026, 10:15 p.m. |
Created at: March 27, 2026, 4:05 p.m.