Triple
T1284610
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Meso-Melanesian languages |
E27405
|
entity |
| Predicate | hasMemberLanguage |
P7390
|
FINISHED |
| Object |
Tigak
Tigak is an Austronesian language of the Meso-Melanesian subgroup spoken primarily in parts of Papua New Guinea.
|
E146926
|
NE FINISHED |
How this triple was built (4 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: Tigak | Statement: [Meso-Melanesian languages, hasMemberLanguage, Tigak]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tigak Context triple: [Meso-Melanesian languages, hasMemberLanguage, Tigak]
-
A.
Tama
Tama is a region in western Tokyo, Japan, encompassing several suburban cities and towns that serve as residential and commercial areas for the greater Tokyo metropolis.
-
B.
Watugaluh
Watugaluh was an important historical city in Java that served as the political and administrative center of the Medang Kingdom.
-
C.
Pekat
Pekat is a settlement on the Indonesian island of Sumbawa that was devastated by the catastrophic 1815 eruption of Mount Tambora.
-
D.
Kawki
Kawki is an indigenous Andean language closely related to Aymara and spoken by a small number of people in Peru.
-
E.
Takanot
Takanot are rabbinic enactments or decrees established to address communal needs and clarify or safeguard Jewish law within Rabbinic Judaism.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Tigak Triple: [Meso-Melanesian languages, hasMemberLanguage, Tigak]
Generated description
Tigak is an Austronesian language of the Meso-Melanesian subgroup spoken primarily in parts of Papua New Guinea.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tigak Target entity description: Tigak is an Austronesian language of the Meso-Melanesian subgroup spoken primarily in parts of Papua New Guinea.
-
A.
Tama
Tama is a region in western Tokyo, Japan, encompassing several suburban cities and towns that serve as residential and commercial areas for the greater Tokyo metropolis.
-
B.
Watugaluh
Watugaluh was an important historical city in Java that served as the political and administrative center of the Medang Kingdom.
-
C.
Pekat
Pekat is a settlement on the Indonesian island of Sumbawa that was devastated by the catastrophic 1815 eruption of Mount Tambora.
-
D.
Kawki
Kawki is an indigenous Andean language closely related to Aymara and spoken by a small number of people in Peru.
-
E.
Takanot
Takanot are rabbinic enactments or decrees established to address communal needs and clarify or safeguard Jewish law within Rabbinic Judaism.
- F. None of above. chosen
Provenance (5 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_69a496d4ec448190ad653b2590c46711 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c0b6dda48190a2e79084adea6ec1 |
completed | March 1, 2026, 10:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69aca2fdb3ac81909bc836e2a655130c |
completed | March 7, 2026, 10:13 p.m. |
| NEDg | Description generation | batch_69aca76c18d081908154d2a04c7a3328 |
completed | March 7, 2026, 10:32 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69aca7d3c740819084c87134e5818455 |
completed | March 7, 2026, 10:33 p.m. |
Created at: March 1, 2026, 7:50 p.m.