Triple

T17777548
Position Surface form Disambiguated ID Type / Status
Subject Observatorio station E443810 entity
Predicate hasStationCode P1289 FINISHED
Object OBV
OBV is the station code for Observatorio, a metro station in Mexico City’s rapid transit system.
 E1286654 NE FINISHED

How this triple was built (4 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: OBV | Statement: [Observatorio station, hasStationCode, OBV]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: OBV
Context triple: [Observatorio station, hasStationCode, OBV]
  • A. OVB
    OVB is the IATA airport code for Tolmachevo Airport, the main international airport serving Novosibirsk, Russia.
  • B. Cboe Volatility Index (VIX)
    The Cboe Volatility Index (VIX) is a widely followed financial benchmark that measures the stock market’s expectation of near-term volatility, often referred to as the market’s “fear gauge.”
  • C. OBX Index
    The OBX Index is a benchmark stock market index that tracks the performance of the most liquid and traded companies listed on the Oslo Stock Exchange in Norway.
  • D. ICE Liquidity Indicators
    ICE Liquidity Indicators is a financial analytics product that estimates and measures the liquidity and tradability of securities across global markets.
  • E. OVL
    OVL is the three-letter National Rail station code used to identify Oval Underground Station on London's public transport network.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: OBV
Triple: [Observatorio station, hasStationCode, OBV]
Generated description
OBV is the station code for Observatorio, a metro station in Mexico City’s rapid transit system.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: OBV
Target entity description: OBV is the station code for Observatorio, a metro station in Mexico City’s rapid transit system.
  • A. OVB
    OVB is the IATA airport code for Tolmachevo Airport, the main international airport serving Novosibirsk, Russia.
  • B. Cboe Volatility Index (VIX)
    The Cboe Volatility Index (VIX) is a widely followed financial benchmark that measures the stock market’s expectation of near-term volatility, often referred to as the market’s “fear gauge.”
  • C. OBX Index
    The OBX Index is a benchmark stock market index that tracks the performance of the most liquid and traded companies listed on the Oslo Stock Exchange in Norway.
  • D. ICE Liquidity Indicators
    ICE Liquidity Indicators is a financial analytics product that estimates and measures the liquidity and tradability of securities across global markets.
  • E. OVL
    OVL is the three-letter National Rail station code used to identify Oval Underground Station on London's public transport network.
  • F. None of above. chosen

Provenance (5 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_69d8b9ef17708190bdf7e2adbf14ddc2 completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e4871e06a481909cf6d59e49dc21c5 completed April 19, 2026, 7:41 a.m.
NED1 Entity disambiguation (via context triple) batch_6a02efc9c0e88190977da0421df6b1a7 completed May 12, 2026, 9:15 a.m.
NEDg Description generation batch_6a02f08892e08190a75c4e523366feda completed May 12, 2026, 9:19 a.m.
NED2 Entity disambiguation (via description) batch_6a02f18036788190ad1a2893fd104261 completed May 12, 2026, 9:23 a.m.
Created at: April 10, 2026, 10:12 a.m.