Triple
T1898057
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shanghai Railway Station |
E37626
|
entity |
| Predicate | railwayStationCode |
P1289
|
FINISHED |
| Object | SHH |
E193132
|
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: SHH | Statement: [Shanghai Railway Station, railwayStationCode, SHH]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SHH Context triple: [Shanghai Railway Station, railwayStationCode, SHH]
-
A.
SHH
chosen
SHH is the railway station code used to identify Shanghai South Railway Station in China’s rail network.
-
B.
Hish
Hish was a field corps branch of the Haganah, the main Jewish paramilitary organization in Mandatory Palestine before the establishment of the State of Israel.
-
C.
CHH
CHH is the vehicle registration code used on license plates for the Mexican state of Chihuahua.
-
D.
HH
HH is the vehicle registration code used on license plates for the German city-state of Hamburg.
-
E.
SHASS
SHASS is the abbreviated name commonly used for the School of Humanities, Arts, and Social Sciences at academic institutions.
- 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_69a8861be7148190a680937ec451a304 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb170657481908662089511a8f301 |
completed | March 7, 2026, 5:02 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adeaf08708819091566511228d8ec8 |
completed | March 8, 2026, 9:32 p.m. |
Created at: March 4, 2026, 7:35 p.m.