Triple
T9029397
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Republic Protocol |
E216130
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | REN |
E41479
|
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: REN | Statement: [Republic Protocol, alsoKnownAs, REN]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: REN Context triple: [Republic Protocol, alsoKnownAs, REN]
-
A.
REN
chosen
REN is a blockchain-based project and protocol focused on enabling cross-chain liquidity and interoperability between different cryptocurrency networks.
-
B.
Ren
Ren is a central character in Margaret Atwood’s dystopian MaddAddam trilogy, known for her experiences as a sex worker and survivor in a bioengineered, post-apocalyptic world.
-
C.
Ren
Ren is a Chinese surname most prominently associated with Ren Zhengfei, the founder of Huawei.
-
D.
RE
RE is the two-letter ISO 3166-1 alpha-2 country code assigned to the French overseas department and region of Réunion.
-
E.
RE
RE is a vehicle registration code used in parts of Austria, including the area around Ehrwald.
- 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_69ca83a5fa88819088144801b4dd7245 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc6a9bcb508190b58751f1772407d4 |
completed | April 1, 2026, 12:45 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfdbc289648190834031537c8ce130 |
completed | April 3, 2026, 3:24 p.m. |
Created at: March 30, 2026, 7:08 p.m.