Triple

T3922548
Position Surface form Disambiguated ID Type / Status
Subject Jefferson Station (SEPTA) E93193 entity
Predicate hasStationCode P1289 FINISHED
Object JEFF
JEFF is the station code used by SEPTA for Jefferson Station, a major regional rail hub in Center City Philadelphia.
 E400230 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: JEFF | Statement: [Jefferson Station (SEPTA), hasStationCode, JEFF]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: JEFF
Context triple: [Jefferson Station (SEPTA), hasStationCode, JEFF]
  • A. Jeff
    Jeff is a masculine given name commonly used in English-speaking countries, often as a short form of Jeffrey or Jefferson.
  • B. Jeffrey
    Jeffrey is a masculine given name of Germanic origin, commonly used in English-speaking countries.
  • C. Jim
    Jim is a common English given name, typically used as a diminutive or familiar form of James.
  • D. Jo
    Jo is a given name used across various cultures, often as a short form of names like Joseph, Joanna, or Jonathan.
  • E. Jerry
    Jerry is one of the two cross-dressing musician protagonists in the classic 1959 comedy film "Some Like It Hot," famously portrayed by Jack Lemmon.
  • 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: JEFF
Triple: [Jefferson Station (SEPTA), hasStationCode, JEFF]
Generated description
JEFF is the station code used by SEPTA for Jefferson Station, a major regional rail hub in Center City Philadelphia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: JEFF
Target entity description: JEFF is the station code used by SEPTA for Jefferson Station, a major regional rail hub in Center City Philadelphia.
  • A. Jeff
    Jeff is a masculine given name commonly used in English-speaking countries, often as a short form of Jeffrey or Jefferson.
  • B. Jeffrey
    Jeffrey is a masculine given name of Germanic origin, commonly used in English-speaking countries.
  • C. Jim
    Jim is a common English given name, typically used as a diminutive or familiar form of James.
  • D. Jo
    Jo is a given name used across various cultures, often as a short form of names like Joseph, Joanna, or Jonathan.
  • E. Jerry
    Jerry is one of the two cross-dressing musician protagonists in the classic 1959 comedy film "Some Like It Hot," famously portrayed by Jack Lemmon.
  • 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_69aed96bfa1081908f7b30f2c647dee6 completed March 9, 2026, 2:30 p.m.
NER Named-entity recognition batch_69aeed7a553c81909b65f8287293ecac completed March 9, 2026, 3:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69b52870268881908463e30c11cda797 completed March 14, 2026, 9:20 a.m.
NEDg Description generation batch_69b52c3d0c0481909e869cf88e3f8a9d completed March 14, 2026, 9:37 a.m.
NED2 Entity disambiguation (via description) batch_69b52cb30f5c819095ac6e101a14b880 completed March 14, 2026, 9:38 a.m.
Created at: March 9, 2026, 3:22 p.m.