Triple
T2960322
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mary |
E80030
|
entity |
| Predicate | historicalAssociation |
P1481
|
FINISHED |
| Object | Merv |
E85087
|
NE 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: Merv | Statement: [Mary, historicalAssociation, Merv]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Merv Context triple: [Mary, historicalAssociation, Merv]
-
A.
Merv
chosen
Merv was an important ancient oasis city in Central Asia that flourished as a key commercial and cultural hub along the Silk Road.
-
B.
Wasilla
Wasilla is a small city in south-central Alaska known as part of the Anchorage metropolitan area and for being the hometown of former governor Sarah Palin.
-
C.
Jowhar
Jowhar is a town in southern Somalia that serves as the capital of the Middle Shabelle region and an important agricultural and administrative center.
-
D.
Mosta
Mosta is a town in central Malta best known for its impressive Rotunda church, which has one of the largest unsupported domes in the world.
-
E.
Mianeh
Mianeh is a significant city in northwestern Iran known as an important urban and transportation center in the East Azerbaijan region.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ad8b1341848190bd19dbf46892887d |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad992dd4248190b5f3d4f342593b8c |
completed | March 8, 2026, 3:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b0fc923d888190a68075dfaa9e90b2 |
completed | March 11, 2026, 5:24 a.m. |
Created at: March 8, 2026, 2:57 p.m.