Triple
T23474637
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pinner tube station |
E570224
|
entity |
| Predicate | hasStationCode |
P1289
|
FINISHED |
| Object | PIN |
—
|
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: PIN | Statement: [Pinner tube station, hasStationCode, PIN]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: PIN Context triple: [Pinner tube station, hasStationCode, PIN]
-
A.
PIN
PIN is the commonly used abbreviation for People in Need, a humanitarian and development non-governmental organization.
-
B.
Pin
chosen
Pin is a slender, pointed fastening device commonly used to secure or attach materials such as fabric or paper.
-
C.
PIN system
The PIN system is India’s nationwide postal indexing scheme that assigns unique numerical codes to geographic areas to streamline mail sorting and delivery.
-
D.
PINS
PINS is the stock ticker symbol for Pinterest, a visual discovery and social media platform where users find and save ideas through images and videos.
-
E.
PIP
PIP is a UK welfare benefit that helps disabled people or those with long-term health conditions cover the extra costs of daily living and mobility.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e245af8a88819084f2704f6d265a92 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1a704e2a48190acb55f77a2124412 |
completed | April 29, 2026, 6:36 a.m. |
Created at: April 17, 2026, 6 p.m.