Triple
T1381226
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | S&P Composite 1500 |
E29340
|
entity |
| Predicate | dataVendorCode |
P508
|
FINISHED |
| Object | SP1500 |
E157310
|
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: SP1500 | Statement: [S&P Composite 1500, dataVendorCode, SP1500]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SP1500 Context triple: [S&P Composite 1500, dataVendorCode, SP1500]
-
A.
SP1500
chosen
SP1500 is the stock market ticker symbol for the S&P Composite 1500 Index, a broad U.S. equity benchmark that combines large-, mid-, and small-cap stocks.
-
B.
SP100
SP100 is the ticker symbol used by data vendors to represent the S&P 100 stock market index, which tracks 100 major blue-chip U.S. companies.
-
C.
S75
S75 is a line of the Berlin S-Bahn urban rail network serving routes within the Berlin metropolitan area.
-
D.
SR 400
SR 400 is a major north–south highway in Georgia that serves as a key commuter and traffic corridor through the Atlanta metropolitan area.
-
E.
S85
S85 is a suburban rail line of the Berlin S-Bahn network serving routes through the German capital and its surrounding areas.
- 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_69a498d883a48190bfdca525296ef7ee |
completed | March 1, 2026, 7:51 p.m. |
| NER | Named-entity recognition | batch_69a4c31b176c8190a896183140c5c8be |
completed | March 1, 2026, 10:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69acde1c7e5c8190a6b999f2d5dce088 |
completed | March 8, 2026, 2:25 a.m. |
Created at: March 1, 2026, 7:59 p.m.