Triple
T17346586
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Taking Rights Seriously |
E421702
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Hard Cases |
—
|
NE ONDG |
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: Hard Cases | Statement: [Taking Rights Seriously, hasPart, Hard Cases]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hard Cases Context triple: [Taking Rights Seriously, hasPart, Hard Cases]
-
A.
Pretty Hard Cases
Pretty Hard Cases is a Canadian television dramedy series that follows two mismatched female detectives tackling major crimes while juggling their complicated personal lives.
-
B.
Guilty as Charged
Guilty as Charged is a 1991 dark comedy film about a vigilante who kidnaps and executes criminals, featuring Caleb James Goddard in its cast.
-
C.
Caso
Caso is a Spanish-language surname borne by various notable individuals, including Mexican archaeologist and anthropologist Alfonso Caso.
-
D.
Cold Case
Cold Case is an American police procedural television series that follows a team of detectives who investigate and solve long-unsolved murders using modern forensic techniques and fresh witness interviews.
-
E.
Case Black
Case Black was a major World War II Axis offensive in 1943 aimed at crushing the Yugoslav Partisan resistance movement.
- 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: Hard Cases Triple: [Taking Rights Seriously, hasPart, Hard Cases]
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hard Cases Target entity description: Hard Cases is a chapter in Ronald Dworkin’s influential legal philosophy book "Taking Rights Seriously," where he develops his theory of judicial decision-making in difficult or borderline legal disputes.
-
A.
Pretty Hard Cases
Pretty Hard Cases is a Canadian television dramedy series that follows two mismatched female detectives tackling major crimes while juggling their complicated personal lives.
-
B.
Guilty as Charged
Guilty as Charged is a 1991 dark comedy film about a vigilante who kidnaps and executes criminals, featuring Caleb James Goddard in its cast.
-
C.
Caso
Caso is a Spanish-language surname borne by various notable individuals, including Mexican archaeologist and anthropologist Alfonso Caso.
-
D.
Cold Case
Cold Case is an American police procedural television series that follows a team of detectives who investigate and solve long-unsolved murders using modern forensic techniques and fresh witness interviews.
-
E.
Case Black
Case Black was a major World War II Axis offensive in 1943 aimed at crushing the Yugoslav Partisan resistance movement.
- F. None of above. chosen
Provenance (4 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_69d889d520008190a26917a95bf1c2ea |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e43a2923b48190a5d1abd3f535c59f |
completed | April 19, 2026, 2:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0195546198819085804ec0b5b18040 |
completed | May 11, 2026, 8:37 a.m. |
| NEDg | Description generation | batch_6a01965807cc819088792a88b8a099d3 |
in_progress | May 11, 2026, 8:42 a.m. |
Created at: April 10, 2026, 5:44 a.m.