Triple
T35905533
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tai Lü |
E1038460
|
entity |
| Predicate | hasNativeAutonym |
P1435
|
FINISHED |
| Object | ᦅᧄᦺᦑᦟᦹᧉ (in New Tai Lue script) |
—
|
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: ᦅᧄᦺᦑᦟᦹᧉ (in New Tai Lue script) | Statement: [Tai Lü, hasNativeAutonym, ᦅᧄᦺᦑᦟᦹᧉ (in New Tai Lue script)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNativeAutonym Context triple: [Tai Lü, hasNativeAutonym, ᦅᧄᦺᦑᦟᦹᧉ (in New Tai Lue script)]
-
A.
hasEndonym
chosen
Indicates that an entity has a name or designation used by native speakers or within its own local language or community.
-
B.
hasEndonymLanguage
Indicates that the language specified is the one in which a name or term is expressed in its own native or local form.
-
C.
isEndonym
Indicates that a name is used by a group to refer to themselves or their own place/language, rather than being an external or foreign designation.
-
D.
autonymLanguageFamily
Indicates that a language’s self-designated name (autonym) belongs to or is classified within a particular language family.
-
E.
autonymLanguageCode
Indicates that the associated language code is the one used by a language to refer to itself (its autonym).
- 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_69f76e2259608190bf6788a132e0d139 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69ff65987ff88190b09be64f7c0e1da9 |
completed | May 9, 2026, 4:49 p.m. |
| PD | Predicate disambiguation | batch_69ff6525b0548190bef7a9f009e00bb8 |
completed | May 9, 2026, 4:47 p.m. |
Created at: May 3, 2026, 4:07 p.m.