Triple
T4571458
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hammonton |
E123038
|
entity |
| Predicate | isBetween |
P1262
|
FINISHED |
| Object | Philadelphia |
E171
|
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: Philadelphia | Statement: [Hammonton, isBetween, Philadelphia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Philadelphia Context triple: [Hammonton, isBetween, Philadelphia]
-
A.
Philadelphia
Philadelphia is a 1993 American legal drama film that broke ground in mainstream cinema for its portrayal of HIV/AIDS, homophobia, and discrimination in the workplace.
-
B.
Philadelphia
chosen
Philadelphia is a major historic U.S. city in Pennsylvania known for its role in the American Revolution, iconic landmarks like Independence Hall and the Liberty Bell, and its rich cultural and academic institutions.
-
C.
Philadelphia
Philadelphia was the ancient Greco-Roman name of the city now known as Amman, the capital of Jordan.
-
D.
Filadelfia
Filadelfia is a small municipality and town located in the Caldas Department of Colombia, known for its coffee-growing economy in the Andean region.
-
E.
Filadelfia
Filadelfia is a town in the Pando Department of northern Bolivia, located in the Amazon rainforest region near the border with Brazil.
- 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_69bd46466c7081909d07f36be2d08804 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd58c5afa48190bb8505e2cc16e89f |
completed | March 20, 2026, 2:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bdd3cf5e10819099b2927c6f571673 |
completed | March 20, 2026, 11:10 p.m. |
Created at: March 20, 2026, 1:10 p.m.