Triple
T3411390
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PiTaPa |
E71901
|
entity |
| Predicate | compatibleWith |
P203
|
FINISHED |
| Object | TOICA |
E355482
|
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: TOICA | Statement: [PiTaPa, compatibleWith, TOICA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: TOICA Context triple: [PiTaPa, compatibleWith, TOICA]
-
A.
TOICA
chosen
TOICA is a rechargeable contactless smart card used for fare payment on trains and buses in the Nagoya area and other parts of Japan’s JR Central network.
-
B.
Tunechi
Tunechi is a popular nickname and alter ego of American rapper Lil Wayne, often used to refer to his distinctive persona and musical brand.
-
C.
TOIT
TOIT is the standard abbreviation for ACM Transactions on Internet Technology, a peer-reviewed scholarly journal focusing on research in internet and web technologies.
-
D.
Tairiku Datsū Sakusen
Tairiku Datsū Sakusen was a major 1944 Japanese military offensive in China during World War II, aimed at securing railways, destroying U.S. air bases, and linking Japanese-held territories.
-
E.
Tikkana
Tikkana was a prominent 13th-century Telugu poet and scholar best known for translating a major portion of the Mahabharata into Telugu and helping shape classical Telugu literature.
- 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_69ad85ac312481909e7027ced1456a9f |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb90a76288190b92ef3b26638cd47 |
completed | March 8, 2026, 5:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b3546a73988190aeee83c090aa0bcf |
completed | March 13, 2026, 12:03 a.m. |
Created at: March 8, 2026, 3:15 p.m.